Twin Cities campus

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Twin Cities Campus

Electrical Engineering Ph.D.

Electrical and Computer Engineering
College of Science and Engineering
Link to a list of faculty for this program.
Contact Information
Director of Graduate Studies, Department of Electrical and Computer Engineering, University of Minnesota, 3-166 Keller Hall, 200 Union Street SE, Minneapolis, MN 55455 (612-625-3564; fax: 612-625-4583)
  • Program Type: Doctorate
  • Requirements for this program are current for Spring 2023
  • Length of program in credits: 64
  • This program does not require summer semesters for timely completion.
  • Degree: Doctor of Philosophy
Along with the program-specific requirements listed below, please read the General Information section of this website for requirements that apply to all major fields.
The Department of Electrical and Computer Engineering offers diverse educational programs that encompass nearly all aspects of modern electrical and computer engineering, ranging from the very theoretical system and information theory to highly experimental work in novel device research and microelectronics. Emphases in the major are solid state and physical electronics, surface physics, thin films, sputtering, noise and fluctuation phenomena, quantum electronics, plasma physics, automation, power systems and power electronics theory, wave propagation, communication systems and theory, optics, lasers, fiber optics, magnetism, semiconductor properties and devices, VLSI and WSI engineering in theory and practice, network theory, signal and image processing, and computer and systems engineering. Interdisciplinary work is also available in bioelectrical sciences, control sciences, computer sciences, solar energy, applications of systems theory to urban transportation and economic planning, and biological modeling.
Program Delivery
  • via classroom (the majority of instruction is face-to-face)
  • partially online (between 50% to 80% of instruction is online)
Prerequisites for Admission
The preferred undergraduate GPA for admittance to the program is 3.40.
Other requirements to be completed before admission:
All documents must be submitted electronically. No documents should be mailed to the department or the Graduate Admissions Office. Applicants to the doctoral program must submit a writing sample with their online application. The writing sample should consist of a minimum of one, to a maximum of three, class papers or publications.
Special Application Requirements:
Students are considered for admission beginning fall semester only (except for part-time students living in Minnesota who work in industry who may apply for other terms). The deadline for applying for fall semester is December 1. The GRE test is not required and will not be accepted as part of the application.
International applicants must submit score(s) from one of the following tests:
  • TOEFL
    • Internet Based - Total Score: 79
    • Internet Based - Writing Score: 21
    • Internet Based - Reading Score: 19
  • IELTS
    • Total Score: 6.5
  • MELAB
    • Final score: 80
Key to test abbreviations (TOEFL, IELTS, MELAB).
For an online application or for more information about graduate education admissions, see the General Information section of this website.
Program Requirements
28 credits are required in the major.
12 credits are required outside the major.
24 thesis credits are required.
This program may be completed with a minor.
Use of 4xxx courses toward program requirements is permitted under certain conditions with adviser approval.
A minimum GPA of 3.30 is required for students to remain in good standing.
Non-EE coursework that is cross-listed with Electrical Engineering must be taken with the EE course subject. A minimum of 6 course credits at the 8xxx-level is required. The 8xxx-level courses, with the exception of seminars, directed study, and special investigations, can be from the major or outside field. Application of 4xxx-level coursework to degree requirements is restricted to 9 credits from the courses listed below, of which no more than 6 can be from EE courses. Courses offered on both the A-F and S/N grading basis must be taken A-F, with a minimum grade of C earned for each course. Breadth requirement: To satisfy the breadth requirement as part of the Preliminary Written Exam, students must take at least one course in a breadth area and receive a grade of B+ or above. This requirement is satisfied in consultation with the advisor.
Coursework
Major Coursework (14 credits)
Select 14 credits from the following in consultation with the advisor:
EE 5121 - Transistor Device Modeling for Circuit Simulation (3.0 cr)
EE 5141 - Introduction to Microsystem Technology (4.0 cr)
EE 5163 - Semiconductor Properties and Devices I (3.0 cr)
EE 5164 - Semiconductor Properties and Devices II (3.0 cr)
EE 5171 - Microelectronic Fabrication (3.0 cr)
EE 5173 - Basic Microelectronics Laboratory (1.0 cr)
EE 5181 - Micro and Nanotechnology by Self Assembly (3.0 cr)
EE 5231 - Linear Systems and Control (3.0 cr)
EE 5235 - Robust Control System Design (3.0 cr)
EE 5239 - Introduction to Nonlinear Optimization (3.0 cr)
EE 5251 - Optimal Filtering and Estimation (3.0 cr)
EE 5271 - Robot Vision (3.0 cr)
EE 5301 - VLSI Design Automation I (3.0 cr)
EE 5302 - VLSI Design Automation II (3.0 cr)
EE 5323 - VLSI Design I (3.0 cr)
EE 5324 - VLSI Design II (3.0 cr)
EE 5327 - VLSI Design Laboratory (3.0 cr)
EE 5329 - VLSI Digital Signal Processing Systems (3.0 cr)
EE 5333 - Analog Integrated Circuit Design (3.0 cr)
EE 5351 - Applied Parallel Programming (3.0 cr)
EE 5364 - Advanced Computer Architecture (3.0 cr)
EE 5371 - Computer Systems Performance Measurement and Evaluation (3.0 cr)
EE 5393 - Circuits, Computation, and Biology (3.0 cr)
EE 5501 - Digital Communication (3.0 cr)
EE 5505 - Wireless Communication (3.0 cr)
EE 5531 - Probability and Stochastic Processes (3.0 cr)
EE 5542 - Adaptive Digital Signal Processing (3.0 cr)
EE 5545 - Digital Signal Processing Design (3.0 cr)
EE 5549 - Digital Signal Processing Structures for VLSI (3.0 cr)
EE 5561 - Image Processing and Applications: From linear filters to artificial intelligence (3.0 cr)
EE 5581 - Information Theory and Coding (3.0 cr)
EE 5583 - Error Control Coding (3.0 cr)
EE 5585 - Data Compression (3.0 cr)
EE 5601 - Introduction to RF/Microwave Engineering (3.0 cr)
EE 5602 - RF/Microwave Circuit Design (3.0 cr)
EE 5611 - Plasma-Aided Manufacturing (4.0 cr)
EE 5613 - RF/Microwave Circuit Design Laboratory (2.0 cr)
EE 5616 - Antennas: Theory, Analysis, and Design (3.0 cr)
EE 5621 - Physical Optics (3.0 cr)
EE 5622 - Physical Optics Laboratory (1.0 cr)
EE 5624 - Optical Electronics (4.0 cr)
EE 5627 - Optical Fiber Communication (3.0 cr)
EE 5653 - Physical Principles of Magnetic Materials (3.0 cr)
EE 5655 - Magnetic Recording (3.0 cr)
EE 5657 - Physical Principles of Thin Film Technology (4.0 cr)
EE 5705 - Electric Drives in Sustainable Energy Systems (3.0 cr)
EE 5707 - Electric Drives in Sustainable Energy Systems Laboratory (1.0 cr)
EE 5721 - Power Generation Operation and Control (3.0 cr)
EE 5741 - Advanced Power Electronics (3.0 cr)
EE 5745 - Wind Energy Essentials (2.0 cr)
EE 5940 - Special Topics in Electrical Engineering I (1.0-4.0 cr)
EE 5960 - Special Topics in Electrical Engineering III (1.0-4.0 cr)
EE 8100 - Advanced Topics in Electronics (1.0-3.0 cr)
EE 8141 - Advanced Heterojunction Transistors (3.0 cr)
EE 8161 - Physics of Semiconductors (3.0 cr)
EE 8163 - Quantum Electronics (3.0 cr)
EE 8213 - Advanced System Theory (3.0 cr)
EE 8215 - Nonlinear Systems (3.0 cr)
EE 8231 - Optimization Theory (3.0 cr)
EE 8235 - Advanced Control Topics (3.0 cr)
EE 8300 - Advanced Topics in Computers (1.0-3.0 cr)
EE 8310 - Advanced Topics in VLSI (1.0-3.0 cr)
EE 8320 - Advanced Topics in Design Automation (1.0-3.0 cr)
EE 8331 - CMOS Data Converters: A/D and D/A (3.0 cr)
EE 8337 - Analog Circuits for Wire/Wireless Communications (3.0 cr)
EE 8367 - Parallel Computer Organization (3.0 cr)
EE 8510 - Advanced Topics in Communications (1.0-3.0 cr)
EE 8520 - Advanced Topics in Signal Processing (1.0-3.0 cr)
EE 8551 - Multirate Signal Processing and Applications (3.0 cr)
EE 5571 - Statistical Learning and Inference (3.0 cr)
EE 8591 - Predictive Learning from Data (3.0 cr)
EE 8601 - Advanced Electromagnetic Theory (3.0 cr)
EE 8611 - Plasma Physics (3.0 cr)
EE 8620 - Advanced Topics in Magnetics (1.0-3.0 cr)
EE 8630 - Advanced Topics in Electromagnetics (1.0-3.0 cr)
EE 8725 - Advanced Power System Analysis and Economics (3.0 cr)
EE 8741 - Power Electronics in Power Systems (3.0 cr)
EE 8950 - Advanced Topics in Electrical and Computer Engineering (3.0 cr)
Outside Coursework (12 credits)
Select at least 12 credits from the following in consultation with the advisor. Other courses can be selected with advisor and director of graduate studies approval.
AEM 4203 - Aerospace Propulsion (4.0 cr)
AEM 4290 - Special Topics in Fluid Mechanics (1.0-3.0 cr)
AEM 4301 - Orbital Mechanics (3.0 cr)
AEM 4303W - Flight Dynamics and Control [WI] (3.0 cr)
AEM 4305 - Spacecraft Attitude Dynamics and Control (3.0 cr)
AEM 4331 - Aerospace Vehicle Design (4.0 cr)
AEM 4333 - Aerospace Design: Special Projects (3.0 cr)
AEM 4490 - Special Topics in Aerospace Systems (1.0-3.0 cr)
AEM 4501 - Aerospace Structures (3.0 cr)
AEM 4502 - Computational Structural Analysis (3.0 cr)
AEM 4511 - Mechanics of Composite Materials (3.0 cr)
AEM 4581 - Mechanics of Solids (3.0 cr)
AEM 4590 - Special Topics in Solid Mechanics and Materials (1.0-3.0 cr)
AEM 4601 - Instrumentation Laboratory (3.0 cr)
AEM 4602W - Aeromechanics Laboratory [WI] (4.0 cr)
AEM 5247 - Hypersonic Aerodynamics (3.0 cr)
AEM 5253 - Computational Fluid Mechanics (3.0 cr)
AEM 5333 - Design-to-Flight: Small Uninhabited Aerial Vehicles (3.0 cr)
AEM 5401 - Intermediate Dynamics (3.0 cr)
AEM 5501 - Continuum Mechanics (3.0 cr)
AEM 5503 - Theory of Elasticity (3.0 cr)
AEM 5581 - Mechanics of Solids (3.0 cr)
AEM 5651 - Aeroelasticity (3.0 cr)
AEM 8202 - Fluid Mechanics II (3.0 cr)
AEM 8211 - Theory of Turbulence I (3.0 cr)
AEM 8253 - Computational Methods in Fluid Mechanics (3.0 cr)
AEM 8421 - Robust Multivariable Control Design (3.0 cr)
AEM 8423 - Convex Optimization Methods in Control (3.0 cr)
AEM 8495 - Advanced Topics in Aerospace Systems (1.0-4.0 cr)
BBE 5023 - Process Control and Instrumentation (3.0 cr)
BBE 5333 {Inactive} (4.0 cr)
BBE 5733 - Renewable Energy Technologies (3.0 cr)
BIOC 5361 - Microbial Genomics and Bioinformatics (3.0 cr)
BIOC 5528 - Spectroscopy and Kinetics (4.0 cr)
BIOL 4003 - Genetics (3.0 cr)
BIOL 4004 - Cell Biology (3.0 cr)
BIOL 5272 - Applied Biostatistics (4.0 cr)
BMEN 5001 - Advanced Biomaterials (3.0 cr)
BMEN 5041 - Tissue Engineering (3.0 cr)
BMEN 5101 - Advanced Bioelectricity and Instrumentation (3.0 cr)
BMEN 5111 - Biomedical Ultrasound (3.0 cr)
BMEN 5151 - Introduction to BioMEMS and Medical Microdevices (2.0 cr)
BMEN 5201 - Advanced Biomechanics (3.0 cr)
BMEN 5311 - Advanced Biomedical Transport Processes (3.0 cr)
BMEN 5321 - Microfluidics in Biology and Medicine (3.0 cr)
BMEN 5351 - Cell Engineering (3.0 cr)
BMEN 5401 - Advanced Biomedical Imaging (3.0 cr)
BMEN 5411 - Neural Engineering (3.0 cr)
BMEN 5412 - Neuromodulation (3.0 cr)
BMEN 5413 - Neural Decoding and Interfacing (3.0 cr)
BMEN 5421 - Introduction to Biomedical Optics (3.0 cr)
BMEN 5501 - Biology for Biomedical Engineers (3.0 cr)
BMEN 5701 - Cancer Bioengineering (3.0 cr)
BMEN 8001 - Polymeric Biomaterials (3.0 cr)
BMEN 8041 - Advanced Tissue Engineering Lab (3.0 cr)
BMEN 8101 - Biomedical Digital Signal Processing (3.0 cr)
BMEN 8201 - Advanced Tissue Mechanics (3.0 cr)
BMEN 8381 - Bioheat and Mass Transfer (3.0 cr)
BMEN 8401 - New Product Design and Business Development (4.0 cr)
BMEN 8402 - New Product Design and Business Development (4.0 cr)
BMEN 8421 - Biophotonics (3.0 cr)
BMEN 8501 - Dynamical Systems in Biology (3.0 cr)
BMEN 8502 - Physiological Control Systems (3.0 cr)
BMEN 8511 - Systems and Synthetic Biology (3.0 cr)
BMEN 8900 - Special Topics in Biomedical Engineering (1.0-4.0 cr)
CEGE 5211 - Highway Design & Traffic Operations (4.0 cr)
CEGE 5411 - Applied Structural Mechanics (3.0 cr)
CHEM 4001 - Chemistry of Biomass and Biomass Conversion to Fuels and Products [ENV] (4.0 cr)
CHEM 4011 - Mechanisms of Chemical Reactions (3.0 cr)
CHEM 4021 - Computational Chemistry (3.0 cr)
CHEM 4066 {Inactive} (3.0 cr)
CHEM 4101 - Modern Instrumental Methods of Chemical Analysis (3.0 cr)
CHEM 4111W - Modern Instrumental Methods of Chemical Analysis Lab [WI] (2.0 cr)
CHEM 4201 - Materials Chemistry (3.0 cr)
CHEM 4214 - Polymers (3.0 cr)
CHEM 4221 - Introduction to Polymer Chemistry (3.0 cr)
CHEM 4223W - Polymer Laboratory [WI] (2.0 cr)
CHEM 4301 - Applied Surface and Colloid Science (3.0 cr)
CHEM 4311W - Advanced Organic Chemistry Lab [WI] (4.0 cr)
CHEM 4321 - Organic Synthesis (3.0 cr)
CHEM 4322 - Advanced Organic Chemistry (3.0 cr)
CHEM 4352 - Physical Organic Chemistry (3.0 cr)
CHEM 4361 - Interpretation of Organic Spectra (3.0 cr)
CHEM 4411 - Introduction to Chemical Biology (3.0 cr)
CHEM 4412 - Chemical Biology of Enzymes (3.0 cr)
CHEM 4501 - Introduction to Thermodynamics, Kinetics, and Statistical Mechanics (3.0 cr)
CHEM 4502 - Introduction to Quantum Mechanics and Spectroscopy (3.0 cr)
CHEM 4511W - Advanced Physical Chemistry Lab [WI] (3.0 cr)
CHEM 4601 - Green Chemistry [ENV] (3.0 cr)
CHEM 4701 - Inorganic Chemistry (3.0 cr)
CHEM 4711W - Advanced Inorganic Chemistry Lab [WI] (3.0 cr)
CHEM 4715 - Physical Inorganic Chemistry (3.0 cr)
CHEM 4725 - Organometallic Chemistry (3.0 cr)
CHEM 4735 - Bioinorganic Chemistry (3.0 cr)
CHEM 4745 - Advanced Inorganic Chemistry (3.0 cr)
CHEM 5755 - X-Ray Crystallography (4.0 cr)
CHEM 8152 - Analytical Spectroscopy (4.0 cr)
CHEM 8201 - Materials Chemistry (4.0 cr)
CHEM 8551 - Quantum Mechanics I (4.0 cr)
CHEM 8552 - Quantum Mechanics II (2.0 cr)
CHEN 4214 - Polymers (3.0 cr)
CHEN 4401W - Senior Chemical Engineering Lab [WI] (4.0 cr)
CHEN 4501W - Chemical Engineering Design [WI] (4.0 cr)
CHEN 4601 - Process Control (3.0 cr)
CHEN 4701 - Applied Math (3.0 cr)
CHEN 4702 - Introduction to Rheology (2.0 cr)
CHEN 4704 - Advanced Undergraduate Physical Rate Processes I: Transport (3.0 cr)
CHEN 4708 - Advanced Undergraduate Chemical Rate Processes: Analysis of Chemical Reactors (3.0 cr)
CHEN 5751 - Biochemical Engineering (3.0 cr)
CHEN 5753 - Advanced Biomedical Transport Processes (3.0 cr)
CHEN 5771 - Colloids and Dispersions (3.0 cr)
CHEN 8101 - Fluid Mechanics (3.0 cr)
CHEN 8401 - Physical and Chemical Thermodynamics (3.0 cr)
CHEN 8754 - Systems Analysis of Biological Processes (3.0 cr)
CMB 5200 - Statistical Genetics and Genomics (4.0 cr)
CSCI 4011 - Formal Languages and Automata Theory (4.0 cr)
CSCI 4041 - Algorithms and Data Structures (4.0 cr)
CSCI 4061 - Introduction to Operating Systems (4.0 cr)
CSCI 4131 - Internet Programming (3.0 cr)
CSCI 4211 - Introduction to Computer Networks (3.0 cr)
CSCI 4511W - Introduction to Artificial Intelligence [WI] (4.0 cr)
CSCI 4611 - Programming Interactive Computer Graphics and Games (3.0 cr)
CSCI 4707 - Practice of Database Systems (3.0 cr)
CSCI 4921 - History of Computing [TS, HIS] (3.0 cr)
CSCI 4970W - Advanced Project Laboratory [WI] (3.0 cr)
CSCI 5103 - Operating Systems (3.0 cr)
CSCI 5105 - Introduction to Distributed Systems (3.0 cr)
CSCI 5106 - Programming Languages (3.0 cr)
CSCI 5115 - User Interface Design, Implementation and Evaluation (3.0 cr)
CSCI 5125 - Collaborative and Social Computing (3.0 cr)
CSCI 5143 - Real-Time and Embedded Systems (3.0 cr)
CSCI 5161 - Introduction to Compilers (3.0 cr)
CSCI 5211 - Data Communications and Computer Networks (3.0 cr)
CSCI 5221 - Foundations of Advanced Networking (3.0 cr)
CSCI 5271 - Introduction to Computer Security (3.0 cr)
CSCI 5302 - Analysis of Numerical Algorithms (3.0 cr)
CSCI 5304 - Computational Aspects of Matrix Theory (3.0 cr)
CSCI 5421 - Advanced Algorithms and Data Structures (3.0 cr)
CSCI 5451 - Introduction to Parallel Computing: Architectures, Algorithms, and Programming (3.0 cr)
CSCI 5461 - Functional Genomics, Systems Biology, and Bioinformatics (3.0 cr)
CSCI 5471 - Modern Cryptography (3.0 cr)
CSCI 5481 - Computational Techniques for Genomics (3.0 cr)
CSCI 5511 - Artificial Intelligence I (3.0 cr)
CSCI 5512 - Artificial Intelligence II (3.0 cr)
CSCI 5521 - Machine Learning Fundamentals (3.0 cr)
CSCI 5523 - Introduction to Data Mining (3.0 cr)
CSCI 5525 - Machine Learning: Analysis and Methods (3.0 cr)
CSCI 5551 - Introduction to Intelligent Robotic Systems (3.0 cr)
CSCI 5552 - Sensing and Estimation in Robotics (3.0 cr)
CSCI 5561 - Computer Vision (3.0 cr)
CSCI 5607 - Fundamentals of Computer Graphics 1 (3.0 cr)
CSCI 5608 - Fundamentals of Computer Graphics II (3.0 cr)
CSCI 5609 - Visualization (3.0 cr)
CSCI 5611 - Animation & Planning in Games (3.0 cr)
CSCI 5619 - Virtual Reality and 3D Interaction (3.0 cr)
CSCI 5707 - Principles of Database Systems (3.0 cr)
CSCI 5708 - Architecture and Implementation of Database Management Systems (3.0 cr)
CSCI 5801 - Software Engineering I (3.0 cr)
CSCI 5802 - Software Engineering II (3.0 cr)
CSCI 8161 - Advanced Compiler Techniques (3.0 cr)
CSCI 8211 - Advanced Computer Networks and Their Applications (3.0 cr)
CSCI 8314 - Sparse Matrix Computations (3.0 cr)
CSCI 8363 - Numerical Linear Algebra in Data Exploration (3.0 cr)
CSCI 8980 - Special Advanced Topics in Computer Science (1.0-3.0 cr)
ESCI 5201 - Time-Series Analysis of Geological Phenomena (3.0 cr)
ESCI 5204 - Geostatistics and Inverse Theory (3.0 cr)
ESCI 5302 - Isotope Geology (3.0 cr)
ESCI 5353 - Electron Microprobe Theory and Practice (3.0 cr)
GCD 5036 - Molecular Cell Biology (3.0 cr)
IE 5111 - Systems Engineering I (2.0 cr)
IE 5113 - Systems Engineering II (4.0 cr)
IE 5441 - Financial Decision Making (4.0 cr)
IE 8531 - Discrete Optimization (4.0 cr)
IE 8532 - Stochastic Processes and Queuing Systems (4.0 cr)
IE 8534 - Advanced Topics in Operations Research (1.0-4.0 cr)
MATH 4065 - Theory of Interest (4.0 cr)
MATH 4152 - Elementary Mathematical Logic (3.0 cr)
MATH 4242 - Applied Linear Algebra (4.0 cr)
MATH 4281 - Introduction to Modern Algebra (4.0 cr)
MATH 4428 - Mathematical Modeling (4.0 cr)
MATH 4512 - Differential Equations with Applications (3.0 cr)
MATH 4567 - Applied Fourier Analysis (4.0 cr)
MATH 4603 - Advanced Calculus I (4.0 cr)
MATH 4604 - Advanced Calculus II (4.0 cr)
MATH 4653 - Elementary Probability (4.0 cr)
MATH 4707 - Introduction to Combinatorics and Graph Theory (4.0 cr)
MATH 4990 - Topics in Mathematics (1.0-4.0 cr)
MATH 5067 - Actuarial Mathematics I (4.0 cr)
MATH 5068 - Actuarial Mathematics II (4.0 cr)
MATH 5075 - Mathematics of Options, Futures, and Derivative Securities I (4.0 cr)
MATH 5076 - Mathematics of Options, Futures, and Derivative Securities II (4.0 cr)
MATH 5165 - Mathematical Logic I (4.0 cr)
MATH 5248 - Cryptology and Number Theory (4.0 cr)
MATH 5251 - Error-Correcting Codes, Finite Fields, Algebraic Curves (4.0 cr)
MATH 5335 - Geometry I (4.0 cr)
MATH 5378 - Differential Geometry (4.0 cr)
MATH 5385 - Introduction to Computational Algebraic Geometry (4.0 cr)
MATH 5445 - Mathematical Analysis of Biological Networks (4.0 cr)
MATH 5447 - Theoretical Neuroscience (4.0 cr)
MATH 5467 - Introduction to the Mathematics of Image and Data Analysis (4.0 cr)
MATH 5485 - Introduction to Numerical Methods I (4.0 cr)
MATH 5486 - Introduction To Numerical Methods II (4.0 cr)
MATH 5525 - Introduction to Ordinary Differential Equations (4.0 cr)
MATH 5535 - Dynamical Systems and Chaos (4.0 cr)
MATH 5583 - Complex Analysis (4.0 cr)
MATH 5587 - Elementary Partial Differential Equations I (4.0 cr)
MATH 5588 - Elementary Partial Differential Equations II (4.0 cr)
MATH 5651 - Basic Theory of Probability and Statistics (4.0 cr)
MATH 5652 - Introduction to Stochastic Processes (4.0 cr)
MATH 5654 - Prediction and Filtering (4.0 cr)
MATH 5705 - Enumerative Combinatorics (4.0 cr)
MATH 5707 - Graph Theory and Non-enumerative Combinatorics (4.0 cr)
MATH 5711 - Linear Programming and Combinatorial Optimization (4.0 cr)
MATH 8301 - Manifolds and Topology (3.0 cr)
MATH 8302 - Manifolds and Topology (3.0 cr)
MATH 8401 - Mathematical Modeling and Methods of Applied Mathematics (3.0 cr)
MATH 8402 - Mathematical Modeling and Methods of Applied Mathematics (3.0 cr)
MATH 8442 - Numerical Analysis and Scientific Computing (3.0 cr)
MATH 8445 - Numerical Analysis of Differential Equations (3.0 cr)
MATH 8450 - Topics in Numerical Analysis (1.0-3.0 cr)
MATH 8600 - Topics in Advanced Applied Mathematics (1.0-3.0 cr)
MATH 8601 - Real Analysis (3.0 cr)
MATH 8602 - Real Analysis (3.0 cr)
MATH 8651 - Theory of Probability Including Measure Theory (3.0 cr)
MATH 8668 - Combinatorial Theory (3.0 cr)
MATS 5517 - Microscopy of Materials (3.0 cr)
MATS 5531 {Inactive} (3.0 cr)
MATS 5771 - Colloids and Dispersions (3.0 cr)
MATS 8001 - Structure and Symmetry of Materials (3.0 cr)
MATS 8003 - Electronic Properties (3.0 cr)
MATS 8995 - Special Topics (1.0-4.0 cr)
ME 5113 - Aerosol/Particle Engineering (4.0 cr)
ME 5223 - Materials in Design (4.0 cr)
ME 5228 - Introduction to Finite Element Modeling, Analysis, and Design (4.0 cr)
ME 5241 - Computer-Aided Engineering (4.0 cr)
ME 5243 - Advanced Mechanism Design (4.0 cr)
ME 5247 - Applied Stress Analysis (4.0 cr)
ME 5281 - Feedback Control Systems (4.0 cr)
ME 5286 - Robotics (4.0 cr)
ME 5312 - Solar Thermal Technologies (4.0 cr)
ME 5344 - Thermodynamics of Fluid Flow With Applications (4.0 cr)
ME 5351 - Computational Heat Transfer (4.0 cr)
ME 5461 - Internal Combustion Engines (4.0 cr)
ME 8228 - Finite Elements in Multidisciplinary Flow/Thermal/Stress and Manufacturing Applications (4.0 cr)
ME 8229 - Finite Element Methods for Computational Mechanics: Transient/Dynamic Problems (4.0 cr)
ME 8243 - Topics in Design: Advanced Materials (4.0 cr)
ME 8253 - Computational Nanomechanics (3.0 cr)
ME 8254 - Fundamentals of Microelectromechanical Systems (MEMS) (4.0 cr)
ME 8281 - Advanced Control System Design-1 (3.0 cr)
ME 8343 - Radiation (3.0 cr)
MPHY 5170 - Radiation Therapy Physics I (3.0 cr)
MPHY 5171 - Medical and Health Physics of Imaging I (3.0 cr)
MPHY 5174 - Medical and Health Physics of Imaging II (3.0 cr)
MPHY 8147 - Advanced Physics of Magnetic Resonance Imaging (MRI) (3.0 cr)
NPSE 8101 - Nanoparticle Science and Engineering Seminar (1.0 cr)
NSC 5040 - Brain Networks: From Connectivity to Dynamics (4.0 cr)
NSC 5202 - Theoretical Neuroscience: Systems and Information Processing (3.0 cr)
NSC 5203 - Basic and Clinical Vision Science (3.0 cr)
NSC 5561 - Systems Neuroscience (4.0 cr)
PHSL 5061 - Principles of Physiology for Biomedical Engineering (4.0 cr)
PHSL 5101 - Human Physiology (5.0 cr)
PHSL 5201 - Computational Neuroscience I: Membranes and Channels (3.0 cr)
PHYS 4001 - Analytical Mechanics (4.0 cr)
PHYS 4002 - Electricity and Magnetism (4.0 cr)
PHYS 4041 - Computational Methods in the Physical Sciences (4.0 cr)
PHYS 4051 - Methods of Experimental Physics I (5.0 cr)
PHYS 4052W - Methods of Experimental Physics II [WI] (5.0 cr)
PHYS 4101 - Quantum Mechanics (4.0 cr)
PHYS 4121W - History of 20th-Century Physics [WI] (3.0 cr)
PHYS 4201 - Statistical and Thermal Physics (3.0 cr)
PHYS 4211 - Introduction to Solid-State Physics (3.0 cr)
PHYS 4303 - Electrodynamics and Waves (3.0 cr)
PHYS 4511 - Introduction to Nuclear and Particle Physics (3.0 cr)
PHYS 4611 - Introduction to Space Physics (3.0 cr)
PHYS 4621 - Introduction to Plasma Physics (3.0 cr)
PHYS 4911 - Introduction to Biopolymer Physics (3.0 cr)
PHYS 5001 - Quantum Mechanics I (4.0 cr)
PHYS 5002 - Quantum Mechanics II (4.0 cr)
PHYS 5011 - Classical Physics I (4.0 cr)
PHYS 5012 - Classical Physics II (4.0 cr)
PHYS 5041 - Mathematical Methods for Physics (4.0 cr)
PHYS 5081 - Introduction to Biopolymer Physics (3.0 cr)
PHYS 5201 - Thermal and Statistical Physics (3.0 cr)
PHYS 5701 - Solid-State Physics for Engineers and Scientists (4.0 cr)
PHYS 8001 - Advanced Quantum Mechanics (3.0 cr)
PHYS 8711 - Solid-State Physics I (3.0 cr)
PHYS 8712 - Solid-State Physics II (3.0 cr)
PMB 4121 - Microbial Ecology and Applied Microbiology (3.0 cr)
PSY 5036W - Computational Vision [WI] (3.0 cr)
PSY 5038W - Introduction to Neural Networks [WI] (3.0 cr)
SSM 5612 - Systems Approach to Building Science and Construction (4.0 cr)
SSM 5614 - Building Systems Performance: Testing & Diagnostics (2.0 cr)
STAT 4101 - Theory of Statistics I (4.0 cr)
STAT 4102 - Theory of Statistics II (4.0 cr)
STAT 5021 - Statistical Analysis (4.0 cr)
STAT 5101 - Theory of Statistics I (4.0 cr)
STAT 5102 - Theory of Statistics II (4.0 cr)
STAT 5201 - Sampling Methodology in Finite Populations (3.0 cr)
STAT 5302 - Applied Regression Analysis (4.0 cr)
STAT 5303 - Designing Experiments (4.0 cr)
STAT 5401 - Applied Multivariate Methods (3.0 cr)
STAT 5421 - Analysis of Categorical Data (3.0 cr)
STAT 5511 - Time Series Analysis (3.0 cr)
STAT 8053 - Applied Statistical Methods 3: Multivariate Analysis and Advanced Regression (3.0 cr)
STAT 8054 - Statistical Methods 4: Advanced Statistical Computing (3.0 cr)
STAT 8101 - Theory of Statistics 1 (3.0 cr)
STAT 8111 - Mathematical Statistics I (3.0 cr)
STAT 8501 - Introduction to Stochastic Processes with Applications (3.0 cr)
STAT 8931 - Advanced Topics in Statistics (3.0 cr)
STAT 8932 - Advanced Topics in Statistics (3.0 cr)
Additional Coursework
Select remaining courses in consultation with the advisor to complete the 40 course credits required for the major. Coursework can be EE or non-EE coursework and can be selected from the following list or the above Major Coursework or Outside Coursework lists. A maximum of 2 credits of the following courses may be selected: EE 5041, EE 8190, EE 8210, EE 8230, EE 8360, EE 8370, EE 8500, EE 8610, EE 8660, EE 8920, EE 8925, EE 8940, and MOT 4001.
EE 4111 - Advanced Analog Electronics Design (4.0 cr)
EE 4161W - Energy Conversion and Storage [WI] (3.0 cr)
EE 4163 - Energy Conversion and Storage Laboratory (1.0 cr)
EE 4231 - Linear Control Systems: Designed by Input/Output Methods (3.0 cr)
EE 4233 - State Space Control System Design (3.0 cr)
EE 4235 - Linear Control Systems Laboratory (1.0 cr)
EE 4237 - State Space Control Laboratory (1.0 cr)
EE 4301 - Digital Design With Programmable Logic (4.0 cr)
EE 4303 - Introduction to Programmable Devices Laboratory (1.0 cr)
EE 4341 - Embedded System Design (4.0 cr)
EE 4363 - Computer Architecture and Machine Organization (4.0 cr)
EE 4389W - Introduction to Predictive Learning [WI] (3.0 cr)
EE 4501 - Communications Systems (3.0 cr)
EE 4505 - Communications Systems Laboratory (1.0 cr)
EE 4541 - Digital Signal Processing (3.0 cr)
EE 4607 - Wireless Hardware System Design (3.0 cr)
EE 4616 - Antennas: Theory, Analysis, and Design (3.0 cr)
EE 4701 - Electric Drives (3.0 cr)
EE 4703 - Electric Drives Laboratory (1.0 cr)
EE 4721 - Introduction to Power System Analysis (3.0 cr)
EE 4722 - Power System Analysis Laboratory (1.0 cr)
EE 4741 - Power Electronics (3.0 cr)
EE 4743 - Switch-Mode Power Electronics Laboratory (1.0 cr)
EE 5041 - Industrial Assignment for Graduate Students (1.0 cr)
EE 8190 - Electronics Seminar (1.0 cr)
EE 8210 - System Theory Seminar (1.0 cr)
EE 8230 - Control Theory Seminar (1.0 cr)
EE 8360 - Computer Systems Seminar (1.0 cr)
EE 8370 - Computer Aided Design Seminar (1.0 cr)
EE 8500 - Seminar: Communications (1.0 cr)
EE 8610 - Seminar: Electronics, Fields, and Photonics (1.0 cr)
EE 8660 - Seminar: Magnetics (1.0 cr)
EE 8920 - Teaching Experience in Electrical and Computer Engineering (1.0 cr)
EE 8925 - Ethics in Electrical and Computer Engineering (1.0 cr)
EE 8940 - Special Investigations (1.0-3.0 cr)
MOT 4001 - Leadership, Professionalism and Business Basics for Engineers (2.0 cr)
Thesis Credits
Take 24 doctoral thesis credits after passing preliminary oral exam.
EE 8888 - Thesis Credit: Doctoral (1.0-24.0 cr)
 
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EE 5121 - Transistor Device Modeling for Circuit Simulation
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Basics of MOS, bipolar theory. Evolution of popular device models from early SPICE models to current industry standards. prereq: [3115, 3161, CSE grad student] or dept consent
EE 5141 - Introduction to Microsystem Technology
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Microelectromechanical systems composed of microsensors, microactuators, and electronics integrated onto common substrate. Design, fabrication, and operation principles. Labs on micromachining, photolithography, etching, thin film deposition, metallization, packaging, and device characterization. prereq: [3161, 3601, CSE grad student] or dept consent
EE 5163 - Semiconductor Properties and Devices I
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Principles/properties of semiconductor devices. Selected topics in semiconductor materials, statistics, and transport. Aspects of transport in p-n junctions, heterojunctions. prereq: [3161, 3601, CSE grad student] or dept consent
EE 5164 - Semiconductor Properties and Devices II
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Principles/properties of semiconductor devices. Charge control in different FETs, transport, modeling. Bipolar transistor models (Ebers-Moll, Gummel-Poon), heterostructure bipolar transistors. Special devices. prereq: 5163 or instr consent
EE 5171 - Microelectronic Fabrication
Credits: 3.0 [max 4.0]
Typically offered: Every Fall
Fabrication of microelectronic devices. Silicon integrated circuits, GaAs devices. Lithography, oxidation, diffusion. Process integration of various technologies, including CMOS, double poly bipolar, and GaAs MESFET. prereq: CSE grad student or dept consent
EE 5173 - Basic Microelectronics Laboratory
Credits: 1.0 [max 1.0]
Typically offered: Every Fall
Students fabricate a polysilicon gate, single-layer metal, NMOS chip, performing 80 percent of processing, including photolithography, diffusion, oxidation, and etching. In-process measurement results are compared with final electrical test results. Simple circuits are used to estimate technology performance. prereq: [[5171 or concurrent registration is required (or allowed) in 5171], CSE grad student] or dept consent
EE 5181 - Micro and Nanotechnology by Self Assembly
Credits: 3.0 [max 3.0]
Typically offered: Spring Odd Year
Self-assembly process of micro and nano structures for realization of 1-, 2-, 3-dimensional micro- and nano-devices. Micro and nanoscale fabrication by electrostatic, magnetic, surface tension, Capillary, intrinsic and extrinsic forces. Nanoscale lithographic patterning. Devices packaging, Self-healing process. prereq: EE 3161, Phys 1302
EE 5231 - Linear Systems and Control
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
The course studies finite-dimensional linear systems in continuous and discrete time. Such systems are described by ordinary differential and difference equations. Input-output and state-space descriptions are provided and analyzed. Introductory methods for controlling such systems are developed. prereq: [3015, CSE grad student] or instr consent
EE 5235 - Robust Control System Design
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Development of control system design ideas; frequency response techniques in design of single-input/single-output (and MI/MO) systems. Robust control concepts. CAD tools. prereq: CSE grad, 3015, 5231 or instr consent
EE 5239 - Introduction to Nonlinear Optimization
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Nonlinear optimization. Analytical/computational methods. Constrained optimization methods. Convex analysis, Lagrangian relaxation, non-differentiable optimization, applications in integer programming. Optimality conditions, Lagrange multiplier theory, duality theory. Control, communications, management science applications. prereq: [3025, Math 2373, Math 2374, CSE grad student] or dept consent
EE 5251 - Optimal Filtering and Estimation
Credits: 3.0 [max 3.0]
Course Equivalencies: AEM 5451/EE 5251
Typically offered: Every Fall
Basic probability theory, stochastic processes. Gauss-Markov model. Batch/recursive least squares estimation. Filtering of linear/nonlinear systems. Continuous-time Kalman-Bucy filter. Unscented Kalman filter, particle filters. Applications. prereq: [[[MATH 2243, STAT 3021] or equiv], CSE grad student] or dept consent; 3025, 4231 recommended
EE 5271 - Robot Vision
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Modern visual perception for robotics that includes position and orientation, camera model and calibration, feature detection, multiple images, pose estimation, vision-based control, convolutional neural networks, reinforcement learning, deep Q-network, and visuomotor policy learning. [Math 2373 or equivalent; EE 1301 or equivalent basic programming course]
EE 5301 - VLSI Design Automation I
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Basic graph/numerical algorithms. Algorithms for logic/high-level synthesis. Simulation algorithms at logic/circuit level. Physical-design algorithms. prereq: [2301, CSE grad student] or dept consent
EE 5302 - VLSI Design Automation II
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Basic algorithms, computational complexity. High-level synthesis. Test generation. Power estimation. Timing optimization. Current topics. prereq: [5301, CSE grad student] or dept consent
EE 5323 - VLSI Design I
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Combinational static CMOS circuits. Transmission gate networks. Clocking strategies, sequential circuits. CMOS process flows, design rules, structured layout techniques. Dynamic circuits, including Domino CMOS and DCVS. Performance analysis, design optimization, device sizing. prereq: [2301, 3115, CSE grad student] or dept consent
EE 5324 - VLSI Design II
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
CMOS arithmetic logic units, high-speed carry chains, fast CMOS multipliers. High-speed performance parallel shifters. CMOS memory cells, array structures, read/write circuits. Design for testability, including scan design and built-in self test. VLSI case studies. prereq: [5323, CSE grad student] or dept consent
EE 5327 - VLSI Design Laboratory
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Complete design of an integrated circuit. Designs evaluated by computer simulation. prereq: [4301, [5323 or concurrent registration is required (or allowed) in 5323], CSE grad student] or dept consent
EE 5329 - VLSI Digital Signal Processing Systems
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Programmable architectures for signal/media processing. Data-flow representation. Architecture transformations. Low-power design. Architectures for two's complement/redundant representation, carry-save, and canonic signed digit. Scheduling/allocation for high-level synthesis. prereq: [[5323 or concurrent registration is required (or allowed) in 5323], CSE grad student] or dept consent
EE 5333 - Analog Integrated Circuit Design
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Fundamental circuits for analog signal processing. Design issues associated with MOS/BJT devices. Design/testing of circuits. Selected topics (e.g., modeling of basic IC components, design of operational amplifier or comparator or analog sampled-data circuit filter). prereq: [3115, CSE grad student] or dept consent
EE 5351 - Applied Parallel Programming
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Parallel programming/architecture. Application development for many-core processors. Computational thinking, types of parallelism, programming models, mapping computations effectively to parallel hardware, efficient data structures, paradigms for efficient parallel algorithms, application case studies. prereq: [4363 or equivalent], programming experience (C/C++ preferred)
EE 5364 - Advanced Computer Architecture
Credits: 3.0 [max 3.0]
Course Equivalencies: CSci 5204/EE 5364
Typically offered: Every Fall
Instruction set architecture, processor microarchitecture. Memory and I/O systems. Interactions between computer software and hardware. Methodologies of computer design. prereq: [[4363 or CSci 4203], CSE grad student] or dept consent
EE 5371 - Computer Systems Performance Measurement and Evaluation
Credits: 3.0 [max 3.0]
Course Equivalencies: EE 5371/5863
Typically offered: Periodic Fall & Spring
Tools/techniques for analyzing computer hardware, software, system performance. Benchmark programs, measurement tools, performance metrics. Deterministic/probabilistic simulation techniques, random number generation/testing. Bottleneck analysis. prereq: [4363 or 5361 or CSci 4203 or 5201], [CSE grad student] or dept consent
EE 5393 - Circuits, Computation, and Biology
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Connections between digital circuit design and synthetic/computational biology. Probabilistic, discrete-event simulation. Timing analysis. Information-Theoretic Analysis. Feedback in digital circuits/genetic regulatory systems. Synthesizing stochastic logic and probabilistic biochemistry.
EE 5501 - Digital Communication
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Theory/techniques of modern digital communications. Communication limits. Modulation/detection. Data transmission over channels with intersymbol interference. Optimal/suboptimal sequence detection. Equalization. Error correction coding. Trellis-coded modulation. Multiple access. prereq: [3025, 4501, CSE grad student] or dept consent
EE 5505 - Wireless Communication
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Introduction to wireless communication systems. Propagation modeling, digital communication over fading channels, diversity and spread spectrum techniques, radio mobile cellular systems design, performance evaluation. Current European, North American, and Japanese wireless networks. prereq: [4501, CSE grad student] or dept consent; 5501 recommended
EE 5531 - Probability and Stochastic Processes
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Probability, random variables and random processes. System response to random inputs. Gaussian, Markov and other processes for modeling and engineering applications. Correlation and spectral analysis. Estimation principles. Examples from digital communications and computer networks. prereq: [3025, CSE grad student] or dept consent
EE 5542 - Adaptive Digital Signal Processing
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Design, application, and implementation of optimum/adaptive discrete-time FIR/IIR filters. Wiener, Kalman, and Least-Squares. Linear prediction. Lattice structure. LMS, RLS, and Levinson-Durbin algorithms. Channel equalization, system identification, biomedical/sensor array processing, spectrum estimation. Noise cancellation applications. prereq: [4541, 5531, CSE grad student] or dept consent
EE 5545 - Digital Signal Processing Design
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Real-time implementation of digital signal processing (DSP) algorithms, including filtering, sample-rate conversion, and FFT-based spectral analysis. Implementation on a modern DSP Platform. Processor architecture. Arithmetic operations. Real-time processing issues. Processor limitations. Integral laboratory. prereq: [4541, CSE grad student] or dept consent
EE 5549 - Digital Signal Processing Structures for VLSI
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Pipelining. Parallel processing. Fast convolution. FIR, rank-order, IIR, lattice, adaptive digital filters. Scaling and roundoff noise. DCT. Viterbi coders. Lossless coders, video compression. prereq: [4541, CSE grad student] or dept consent
EE 5561 - Image Processing and Applications: From linear filters to artificial intelligence
Credits: 3.0 [max 3.0]
Course Equivalencies: EE 5561/EE 8541
Typically offered: Every Spring
Image enhancement, denoising, segmentation, registration, and computational imaging. Sampling, quantization, morphological processing, 2D image transforms, linear filtering, sparsity and compression, statistical modeling, optimization methods, multiresolution techniques, artificial intelligence concepts, neural networks and their applications in classification and regression tasks in image processing. Emphasis is on the principles of image processing. Implementation of algorithms in Matlab/Python and using deep learning frameworks. prereq: [4541, 5581, CSE grad student] or instr consent
EE 5581 - Information Theory and Coding
Credits: 3.0 [max 3.0]
Typically offered: Fall Even Year
Source/channel models, codes for sources/channels. Entropy, mutual information, capacity, rate-distortion functions. Coding theorems. prereq: [5531, CSE grad student] or dept consent
EE 5583 - Error Control Coding
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Error-correcting codes. Concepts, properties, polynomial representation. BCH, Golay, Reed-Muller/Reed-Solomon codes. Convolutional codes. Iterative codes. prereq: [[3025, Math 2373] or equiv], [CSE grad student or dept consent]
EE 5585 - Data Compression
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Source coding in digital communications and recording. Codes for lossless compression. Universal lossless codes. Lossless image compression. Scalar and vector quantizer design. Loss source coding theory. Differential coding, trellis codes, transform/subband coding. Analysis/synthesis schemes. prereq: CSE grad student or dept consent
EE 5601 - Introduction to RF/Microwave Engineering
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Fundamentals of EM theory and transmission lines concepts. Transmission lines and network analysis. CAD tool. Lumped circuit component designs. Passive circuit components. Connectivity to central communication theme. prereq: [3601, CSE grad student] or dept consent
EE 5602 - RF/Microwave Circuit Design
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Transmission lines, network analysis concepts. CAD tools for passive/active designs. Diode based circuit designs (detectors, frequency multipliers, mixers). Transistor based circuit design (amplifiers, oscillators, mixer/doubler). prereq: [5601 or equiv], [CSE grad student or instr consent]
EE 5611 - Plasma-Aided Manufacturing
Credits: 4.0 [max 4.0]
Course Equivalencies: EE 5611/ME 5361
Grading Basis: A-F or Aud
Typically offered: Periodic Fall & Spring
Manufacturing using plasma processes. Plasma properties as a processing medium. Plasma spraying, welding and microelectronics processing. Process control and system design; industrial speakers. Cross-disciplinary experience between heat transfer design issues and manufacturing technology. prereq: [[[ME 3321, ME 3322] or equiv], [upper div CSE or grad student]] or dept consent
EE 5613 - RF/Microwave Circuit Design Laboratory
Credits: 2.0 [max 2.0]
Grading Basis: A-F only
Typically offered: Every Spring
Scattering parameters, planar lumped circuits, transmission lines, RF/microwave substrate materials, matching networks/tuning elements, resonators, filters, combiners/dividers, couplers. Integral lab. prereq: [[5601 or concurrent registration is required (or allowed) in 5601], CSE grad student] or dept consent
EE 5616 - Antennas: Theory, Analysis, and Design
Credits: 3.0 [max 3.0]
Course Equivalencies: EE 4616/EE 5616
Typically offered: Every Fall
With the widespread use of cell phones autonomous vehicles, and the coming of the Internet of Things, there is an increasing need to understand wireless communications and radar sensors. A key component of these systems is the antenna. The purpose of this course is to help the student develop knowledge in the area of antennas. This involves understanding the parameters that are used to characterize antennas and how these effect system performance. An important aspect of the course is to provide the student with an understanding of the operating principles behind the most commonly used antennas. This is followed with exposure to basic design principles. These can be used to perform antenna design or can be used as starting points for design using an electromagnetic simulator. As part of the course, students will be exposed to simulator use through homework assignments, and possibly, course project work. prereq: EE 3601 or equivalent
EE 5621 - Physical Optics
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Physical optics principles, including Fourier analysis of optical systems/images, scalar diffraction theory, interferometry, and coherence theory. Diffractive optical elements, holography, astronomical imaging, optical information processing, microoptics. prereq: [3015, CSE grad student] or dept consent
EE 5622 - Physical Optics Laboratory
Credits: 1.0 [max 1.0]
Typically offered: Every Spring
Fundamental optical techniques. Diffraction and optical pattern recognition. Spatial/temporal coherence. Interferometry. Speckle. Coherent/incoherent imaging. Coherent image processing. Fiber Optics. prereq: [[5621 or concurrent registration is required (or allowed) in 5621], CSE grad student] or dept consent
EE 5624 - Optical Electronics
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Fundamentals of lasers, including propagation of Gaussian beams, optical resonators, and theory of laser oscillation. Polarization optics, electro-optic, acousto-optic modulation, nonlinear optics, phase conjugation. prereq: [[3601 or Phys 3002], CSE grad student] or dept consent
EE 5627 - Optical Fiber Communication
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Components/systems aspects of optical fiber communication. Modes of optical fibers. Signal degradation/dispersion. Optical sources/detectors. Digital/analog transmissions systems. Direct/coherent detection. Optical amplifiers. Optical soliton propagation. prereq: [3015, 3601, CSE grad student] or dept consent
EE 5653 - Physical Principles of Magnetic Materials
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Physics of diamagnetism, paramagnetism, ferromagnetism, antiferromagnetism, ferrimagnetism. Ferromagnetic phenomena. Static/dynamic theory of micromagnetics, magneto-optics, and magnetization dynamics. Magnetic material applications. prereq: CSE grad student or dept consent
EE 5655 - Magnetic Recording
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Magnetic fundamentals, recording materials, idealized models of magnetic records/reproduction, analytic models of magnetic record heads, sinusoidal magnetic recording, digital magnetic recording, magnetic recording heads/media, digital recording systems. prereq: CSE grad student or dept consent
EE 5657 - Physical Principles of Thin Film Technology
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Fabrication, characterization, and application of thin film and nanostructured materials and devices. Focuses on vacuum deposition. Materials science. Hands-on, team-based labs.
EE 5705 - Electric Drives in Sustainable Energy Systems
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Role of electric drives in wind-electric systems, inertial storage, elec/hybrid vehicles. AC machines for energy-efficient operation using d-q axis modeling. Vector-/direct-torque-controlled induction motor drives. Permanent-magnet and interior-permanent magnet ac motor drives. Sensorless drives. Voltage space-vector modulation technology. prereq: [4701, CSE grad student] or dept consent
EE 5707 - Electric Drives in Sustainable Energy Systems Laboratory
Credits: 1.0 [max 1.0]
Typically offered: Periodic Spring
Lab to accompany 5705. prereq: 5705 or concurrent registration is required (or allowed) in 5705
EE 5721 - Power Generation Operation and Control
Credits: 3.0 [max 3.0]
Typically offered: Spring Odd Year
Engineering aspects of power system operation. Economic analysis of generation plants & scheduling to minimize total cost of operation. Scheduling of hydro resources and thermal plants with limited fuel supplies. Loss analysis, secure operation. State estimation, optimal power flow. Power system organizations. prereq: [4721, CSE grad student] or dept consent
EE 5741 - Advanced Power Electronics
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Physics of solid-state power devices, passive components, magnetic optimization, advanced topologies. Unity power factor correction circuits, EMI issues, snubbers, soft switching in dc/ac converters. Practical considerations. Very low voltage output converters. Integrated computer simulations. prereq: CSE grad student] or dept consent
EE 5745 - Wind Energy Essentials
Credits: 2.0 [max 2.0]
Typically offered: Every Fall
Design, planning, development/operation of wind energy facilities. Wind turbine generator types, wind forecasting/assessment, wind farm project development, grid integration, wind turbine controls, blade aerodynamics/acoustics, mechanical/hydrostatic transmissions, materials/structural reliability, wind turbine foundations, radar interference, role of public policy in wind energy. prereq: CSE grad student or dept consent
EE 5940 - Special Topics in Electrical Engineering I
Credits: 1.0 -4.0 [max 12.0]
Typically offered: Every Fall, Spring & Summer
Special topics in electrical and computer engineering. Topics vary.
EE 5960 - Special Topics in Electrical Engineering III
Credits: 1.0 -4.0 [max 12.0]
Typically offered: Every Fall & Spring
Special topics in electrical and computer engineering. Topics vary.
EE 8100 - Advanced Topics in Electronics
Credits: 1.0 -3.0 [max 12.0]
Typically offered: Periodic Fall
Topics vary according to needs and staff availability. prereq: instr consent
EE 8141 - Advanced Heterojunction Transistors
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall
Recent developments in device modeling with emphasis on bipolar junction transistors. High-level effects in base and collector regions and their interrelationship. prereq: 5664 or instr consent
EE 8161 - Physics of Semiconductors
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Modern solid-state theory applied to specific semiconductor materials. Influence of band structure and scattering mechanisms upon semiconductor properties. Plasma effects in semiconductors. Mathematical treatments of generation-recombination kinetics, carrier injection, drift, and diffusion. Use of semiconductor properties in devices of current importance. prereq: instr consent
EE 8163 - Quantum Electronics
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall & Spring
Quantum theory of light/laser systems. Planck's radiation law, Einstein's coefficients. Quantum mechanics of atom-radiation interaction. Quantized radiation field. Interaction of quantized field with atoms. Generation/amplification of light. Nonlinear optics. Specific laser systems. Semiconductor lasers. prereq: instr consent
EE 8213 - Advanced System Theory
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall
Generalized linear systems; applications, structural properties, computational approaches, classification, functional behavior, and synthesis. prereq: IT grad student, instr consent
EE 8215 - Nonlinear Systems
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Current topics in stability analysis of nonlinear systems, design of controllers for nonlinear systems, discrete-time and stochastic nonlinear systems. prereq: instr consent
EE 8231 - Optimization Theory
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall
Introduction to optimization in engineering; approximation theory. Least squares estimation, optimal control theory, and computational approaches. prereq: instr consent
EE 8235 - Advanced Control Topics
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Adaptive/learning systems. Optimal/robust control/stabilization. Stability of dynamic systems.
EE 8300 - Advanced Topics in Computers
Credits: 1.0 -3.0 [max 12.0]
Typically offered: Periodic Fall
Topics vary according to needs and staff availability. prereq: instr consent
EE 8310 - Advanced Topics in VLSI
Credits: 1.0 -3.0 [max 12.0]
Typically offered: Periodic Fall
Topics vary according to needs and staff availability. prereq: instr consent
EE 8320 - Advanced Topics in Design Automation
Credits: 1.0 -3.0 [max 12.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall
State-of-the-art automated design tools for electronic system design. Topics vary. prereq: Grad student or instr consent
EE 8331 - CMOS Data Converters: A/D and D/A
Credits: 3.0 [max 3.0]
Typically offered: Every Fall & Spring
Data converters, low power low voltage analog circuits. Basic background in design of CMOS analog-to-digital and digital-to-analog converters. Special circuit design techniques for low power design. Students design/test several design problems. prereq: 5333 or instr consent
EE 8337 - Analog Circuits for Wire/Wireless Communications
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Basic background, advanced design concepts necessary to design integrated CMOS RF circuits. Emphasizes CMOS and RF. Where appropriate, mention is made of bipolar circuits and applications to other communications areas. prereq: 5333
EE 8367 - Parallel Computer Organization
Credits: 3.0 [max 3.0]
Course Equivalencies: CSci 8205/EE 8367
Typically offered: Every Spring
Design/implementation of multiprocessor systems. Parallel machine organization, system design. Differences between parallel, uniprocessor machines. Programming models. Synchronization/communication. Topologies, message routing strategies. Performance optimization techniques. Compiler, system software issues. prereq: 5364 or CSci 5204
EE 8510 - Advanced Topics in Communications
Credits: 1.0 -3.0 [max 12.0]
Typically offered: Periodic Fall
Topics vary according to needs and staff availability. prereq: instr consent
EE 8520 - Advanced Topics in Signal Processing
Credits: 1.0 -3.0 [max 12.0]
Typically offered: Every Spring
Topics vary according to needs and staff availability. prereq: instr consent
EE 8551 - Multirate Signal Processing and Applications
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Multirate discrete-time systems with applications in modern signal and data processing problems. Hilbert Spaces and Linear Operators; Reisz Bases and Frames; Vector Space Representation of Sampling, Interpolation, Time-frequency analysis and wavelets; Filterbanks and Polyphase Structures; Sparsity and redundancy with applications in linear and nonlinear approximation, super-resolution, blind-source separation. prereq: [CSE grad student] or dept consent
EE 5571 - Statistical Learning and Inference
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Deterministic and random approaches to learning and inference from data, with applications to statistical models for estimation, detection, and classification. Algorithms and their performance include minimum-variance unbiased estimators, sufficient statistics, fundamental bounds, (non)linear least-squares, maximum-likelihood, expectation-maximization, nonparametric density estimators, mean-square error and Bayesian estimators, importance sampling, Kalman and particle filtering, sequential probability ratio test, bootstrap, Monte Carlo Markov Chains, and graphical models. prereq: courses in Stochastic Processes (EE 5531) and Digital Signal Processing (EE 4541)
EE 8591 - Predictive Learning from Data
Credits: 3.0 [max 3.0]
Typically offered: Fall Even Year
Methods for estimating dependencies from data have been traditionally explored in such diverse fields as: statistics (multivariate regression and classification), engineering (pattern recognition, system identification), computer science (artificial intelligence, machine learning, data mining) and bioinformatics. Recent interest in learning methods is triggered by the widespread use of digital technology and availability of data. Unfortunately, developments in each field are seldom related to other fields. This course is concerned with estimation of predictive data-analytic models that are estimated using past data, but are used for prediction or decision making with new data. This course will first present general conceptual framework for learning predictive models from data, using Vapnik-Chervonenkis (VC) theoretical framework, and then discuss various methods developed in statistics, pattern recognition and machine learning. Course descriptions will emphasize methodological aspects of machine learning, rather than development of ‘new’ algorithms. prereq: CSE grad student or instr consent
EE 8601 - Advanced Electromagnetic Theory
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall
Aspects of electromagnetic theory. Review of introductory material. Scattering theory, geometric theory of diffraction, integral equation methods, Green's functions. prereq: 4601 or equiv
EE 8611 - Plasma Physics
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall
Plasma theory and charged particle transport phenomena: collision processes, orbit theory, kinetic theory, Boltzmann transport equation, moment (continuity) equations, magnetohydrodynamics, transport properties. Applications of plasma theory to modeling of dc, rf, and microwave discharges. prereq: instr consent
EE 8620 - Advanced Topics in Magnetics
Credits: 1.0 -3.0 [max 12.0]
Typically offered: Periodic Fall
Topics vary according to needs and staff availability. prereq: 5653 or instr consent
EE 8630 - Advanced Topics in Electromagnetics
Credits: 1.0 -3.0 [max 12.0]
Typically offered: Periodic Fall
Topics vary according to needs and staff availability.
EE 8725 - Advanced Power System Analysis and Economics
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall
Solving sets of equations that involve large sparse matrices. Sparse matrix storage, ordering schemes, application to power flow, short circuit calculation, optimal power flow, and state estimation. prereq: 4721, CSE grad student or instr consent
EE 8741 - Power Electronics in Power Systems
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall
Impact of power electronics loads on power quality. Passive and active filters. Active input current wave shaping. HVDC transmission. Static VAR control, energy storage systems. Interconnecting photovoltaic and wind generators. Static phase shifters and circuit breakers for flexible AC transmission (FACTS). prereq: 4741, IT grad student or instr consent
EE 8950 - Advanced Topics in Electrical and Computer Engineering
Credits: 3.0 [max 12.0]
Typically offered: Every Fall & Spring
Topics vary according to needs and staff availability. prereq: Cr ar [may be repeated for cr]; instr consent
AEM 4203 - Aerospace Propulsion
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Basic one-dimensional flows: isentropic, area change, heat addition. Overall performance characteristics of propellers, ramjets, turbojets, turbofans, rockets. Performance analysis of inlets, exhaust nozzles, compressors, burners, and turbines. Rocket flight performance, single-/multi-stage chemical rockets, liquid/solid propellants. prereq: 4202, [CSE upper div or grad student]
AEM 4290 - Special Topics in Fluid Mechanics
Credits: 1.0 -3.0 [max 6.0]
Grading Basis: A-F only
Typically offered: Every Fall, Spring & Summer
Topics vary each semester within the field of Fluid Mechanics prereq: dept consent
AEM 4301 - Orbital Mechanics
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
The two-body problem. Earth-satellite operations, rocket performance, reentry dynamics, space environments, interplanetary trajectories. Numerical simulations. Design project. prereq: [2012 or equiv], [MATH 2373 or equiv], [CSE upper div or grad student]
AEM 4303W - Flight Dynamics and Control (WI)
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Forces/moments, trim, linearization, transfer functions, dynamic response characteristics for aircraft. Aircraft stability/control derivatives, static longitudinal/lateral stability. Phugoid, short period, spiral, roll subsidence, dutch roll modes. Handling qualities. Design project. prereq: [2012, 2301, 3101, [WRIT 1301 or equiv], [CSE upper div or grad student]] or instr consent
AEM 4305 - Spacecraft Attitude Dynamics and Control
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Kinematics/dynamics for six-degree of freedom rigid body motions. Euler's angles/equations. Torque free motion, spin stabilization, dual-spin spacecraft, nutation damping, gyroscopic attitude control, gravity gradient stabilization. Linear systems analysis, Laplace transforms, transfer functions. Linear control theory. PID controllers. prereq: [4301, [3101 or ME 3281 or EE 3015], CSE upper div] or grad student
AEM 4331 - Aerospace Vehicle Design
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Fall
Multidisciplinary student teams perform conceptual designs of aerospace vehicles, components, missions, or systems that incorporate realistic constraints/applicable engineering standards. Papers on professional ethics/contemporary aerospace issues. Oral preliminary/critical design reviews. prereq: [2301, 4202, AEM sr] or instr consent
AEM 4333 - Aerospace Design: Special Projects
Credits: 3.0 [max 6.0]
Typically offered: Every Spring
Student groups design, build, and test aerospace projects. Projects include designs from AEM4331 or projects such as microgravity experiments. Students create and maintain an electronic project data repository, prepare weekly status reports, build and test their design, and prepare a final report. prereq: 4331 or instr consent
AEM 4490 - Special Topics in Aerospace Systems
Credits: 1.0 -3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall, Spring & Summer
Topics vary each semester within the field of Aerospace Systems
AEM 4501 - Aerospace Structures
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Advanced strength of materials analysis of elastic structures with aerospace applications; failure modes and criteria, buckling, matrix methods for analysis, plane truss design; energy and Castigliano methods for statically determinate and indeterminate structures; torsion and bending of asymmetrical thin-walled sections. Design project. prereq: CSE upper div or grad, 3031 or equiv
AEM 4502 - Computational Structural Analysis
Credits: 3.0 [max 3.0]
Typically offered: Fall Even Year
Application of finite element methods to problems in structural analysis. Emphasizes properly posing problems and interpreting calculation results. Use of commercial FEA packages. Introduction to theory of finite elements. prereq: [Grade of at least C in 4501, [CSE upper div or grad student]] or instr consent
AEM 4511 - Mechanics of Composite Materials
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Analysis, design, and applications of laminated and chopped fiber reinforced composites. Micro-/macro-mechanical analysis of elastic constants, failure, and environmental degradation. Design project. prereq: 3031 (or 2031 if MatSci), [CSE upper div or grad student]
AEM 4581 - Mechanics of Solids
Credits: 3.0 [max 3.0]
Course Equivalencies: AEM 4581/AEM 5581
Typically offered: Fall Odd Year
Continuum mechanics in one dimension: kinematics; mass, momentum/energy, constitutive theory. Wave propagation, heat conduction. Strings. Euler-Bernoulli theory. 3-D deformations/stress. Topics from fracture mechanics, structural stability, vibrations, thin films, layered media, smart materials, phase transformations, 3-D elastic wave propagation. Elasticity, viscoelasticity, plasticity. prereq: 3031, [Math 2373 or equiv], [Math 2374 or equiv], CSE upper div
AEM 4590 - Special Topics in Solid Mechanics and Materials
Credits: 1.0 -3.0 [max 6.0]
Grading Basis: A-F only
Typically offered: Every Fall, Spring & Summer
Topics vary each semester within the field of Solid Mechanics and Materials prereq: dept consent
AEM 4601 - Instrumentation Laboratory
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Introduction to lab instrumentation. Computerized data acquisition. Statistical analysis of data. Time series data, spectral analysis. Transducers for measurement of solid, fluid, and dynamical quantities. Design of experiments. prereq: CSci 1113, EE 3005, EE 3006, [upper div BAEM]
AEM 4602W - Aeromechanics Laboratory (WI)
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Experimental methods/design in fluid/solid mechanics. Wind tunnel/water channel experiments with flow visualization, pressure, velocity, force measurements. Measurement of stresses/strains/displacements in solids/ structures: stress concentrations, materials behavior, structural dynamics. Computerized data acquisition/analysis, error analysis, data reduction. Experiment design. Written/oral reports. Lab ethics. Writing intensive. prereq: 4201, 4501, 4601, [WRIT 1301 or equiv], [CSE upper div or grad]
AEM 5247 - Hypersonic Aerodynamics
Credits: 3.0 [max 3.0]
Course Equivalencies: AEM 4247/AEM 5247
Grading Basis: A-F or Aud
Typically offered: Spring Even Year
Importance/properties of hypersonic flow. Hypersonic shock and expansion-wave relations. Local surface inclination methods. Approximate/exact methods for hypersonic inviscid flow fields. Viscous flow: boundary layers, aerodynamic heating, hypersonic viscous interactions, computational methods. Hypersonic propulsion and vehicle design. prereq: 4202 or equiv, CSE grad student
AEM 5253 - Computational Fluid Mechanics
Credits: 3.0 [max 3.0]
Course Equivalencies: AEM 4253/AEM 5253
Prerequisites: [4201 or equiv], [CSci 1113 or equiv], CSE grad student
Grading Basis: A-F or Aud
Typically offered: Every Fall
Introductory concepts in finite difference and finite volume methods as applied to various ordinary/partial differential model equations in fluid mechanics. Fundamentals of spatial discretization and numerical integration. Numerical linear algebra. Introduction to engineering and scientific computing environment. Advanced topics may include finite element methods, spectral methods, grid generation, turbulence modeling. prereq: [4201 or equiv], [CSci 1113 or equiv], CSE grad student
AEM 5333 - Design-to-Flight: Small Uninhabited Aerial Vehicles
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Periodic Spring
Designing, assembling, modeling, simulating, testing/flying of uninhabited aerial vehicles. Rapid prototyping software tools for vehicle modeling. Guidance, navigation, flight control, real-time implementations, hardware-in-the-loop simulations, flight tests. prereq: [[4202, concurrent registration is required (or allowed) in 4303W, 4601] or equiv], instr consent
AEM 5401 - Intermediate Dynamics
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Three-dimensional Newtonian mechanics, kinematics of rigid bodies, dynamics of rigid bodies, generalized coordinates, holonomic constraints, Lagrange equations, applications. prereq: CSE upper div or grad, 2012, Math 2243
AEM 5501 - Continuum Mechanics
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Concepts common to all continuous media; elements of tensor analysis; motion, deformation, vorticity; material derivatives; mass, continuity equation; balance of linear, angular momentum; geometric characterization of stress; constitutive equations. prereq: CSE upper div or grad, 3031, Math 2243 or equiv or instr consent
AEM 5503 - Theory of Elasticity
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Introduction to the theory of elasticity, with emphasis on linear elasticity. Linear and nonlinear strain measures, boundary-value problem for linear elasticity, plane problems in linear elasticity, three dimensional problems in linear elasticity. Topics from nonlinear elasticity, micromechanics, contact problems, fracture mechanics. prereq: 4501 or equiv, Math 2263 or equiv or instr consent
AEM 5581 - Mechanics of Solids
Credits: 3.0 [max 3.0]
Course Equivalencies: AEM 4581/AEM 5581
Typically offered: Fall Odd Year
Continuum mechanics in one dimension: kinematics; mass, momentum/energy, constitutive theory. Wave propagation, heat conduction. Strings. Euler-Bernoulli theory. 3-D deformations/stress. Topics from fracture mechanics, structural stability, vibrations, thin films, layered media, smart materials, phase transformations, 3-D elastic wave propagation. Elasticity, viscoelasticity, plasticity. prereq: 3031 or equiv, [Math 2373 or equiv], [Math 2374 or equiv], [CSE grad student]
AEM 5651 - Aeroelasticity
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Static aeroelastic phenomena, torsional divergence of a lifting surface, control surface reversal. Aeroelastic flutter, unsteady aerodynamics. Problems of gust response, buffeting. Design project. prereq: 4202, 4301, [grad student or CSE upper div]
AEM 8202 - Fluid Mechanics II
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Analysis of incompressible viscous flow; creeping flows; boundary layer flow. prereq: 8201
AEM 8211 - Theory of Turbulence I
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall
Reynolds equations, methods of averaging, elements of stability theory and vortex dynamics; description of large vortical structures in mixing layers and boundary layers; horseshoe vortices; flow visualization. prereq: 8202
AEM 8253 - Computational Methods in Fluid Mechanics
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall
Spatial discretization. Spectral methods. Temporal discretization. Nonlinear sources of error. Incompressible Navier-Stokes equations. Compressible Navier-Stokes equations. prereq: 4201
AEM 8421 - Robust Multivariable Control Design
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Application of robust control theory to aerospace systems. Role of model uncertainty/modeling errors in design process. Control analysis and synthesis, including H[sub2] and H[infinity symbol] optimal control design and structural singular value [Greek letter mu] techniques. prereq: 5321 or equiv
AEM 8423 - Convex Optimization Methods in Control
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall
Practical aspects of convex optimization methods applied to solve design/analysis problems in control theory. prereq: 5321 or EE 5231 or equiv
AEM 8495 - Advanced Topics in Aerospace Systems
Credits: 1.0 -4.0 [max 32.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Individual student projects completed under guidance of a faculty sponsor. prereq: dept consent
BBE 5023 - Process Control and Instrumentation
Credits: 3.0 [max 3.0]
Course Equivalencies: BBE 4023/BBE 5023/CEGE 4416/CE
Typically offered: Every Fall
Fundamental principles in system dynamics/control. Emphasizes process systems and problems faced by process engineers. prereq: Grad student or instr consent
BBE 5733 - Renewable Energy Technologies
Credits: 3.0 [max 3.0]
Course Equivalencies: BBE 4733/CEGE 4513/ChEn 5551
Grading Basis: A-F or Aud
Typically offered: Every Spring
Energy security and its environmental, economic and societal impacts. Current and emerging technologies for production and use, characteristics of renewable energy, key methods for efficient production, current and probable future, and impact on sustainable development. prereq: Grad student or instr consent
BIOC 5361 - Microbial Genomics and Bioinformatics
Credits: 3.0 [max 3.0]
Typically offered: Every Fall & Spring
Introduction to genomics. Emphasizes microbial genomics. Sequencing methods, sequence analysis, genomics databases, genome mapping, prokaryotic horizontal gene transfer, genomics in biotechnology, intellectual property issues. Hands-on introduction to UNIX shell scripting, genomic data analysis using R and Excel in a computer lab setting. prereq: College-level courses in [organic chemistry, biochemistry, microbiology]
BIOC 5528 - Spectroscopy and Kinetics
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Biochemical dynamics from perspectives of kinetics and spectroscopy. Influence of structure, molecular interactions, and chemical transformations on biochemical reactions. Focuses on computational, spectroscopic, and physical methods. Steady-state and transient kinetics. Optical and magnetic resonance spectroscopies. prereq: Intro physical chemistry or equiv; intro biochemistry recommended
BIOL 4003 - Genetics
Credits: 3.0 [max 3.0]
Course Equivalencies: Biol 4003/GCD 3022
Typically offered: Every Fall, Spring & Summer
Genetic information, its transmission from parents to offspring, its expression in cells/organisms, and its course in populations. prereq: Biol 2003/2003H or BioC 3021 or BioC 4331 or grad
BIOL 4004 - Cell Biology
Credits: 3.0 [max 3.0]
Course Equivalencies: Biol 4004/GCD 3033/4005W
Typically offered: Every Fall, Spring & Summer
Processes fundamental to cells. Emphasizes eukaryotic cells. Assembly/function of membranes/organelles. Cell division, cell form/movement, intercellular communication, transport, secretion pathways. Cancer cells, differentiated cells. prereq: Completion of Biol 4003 is preferred, Biol2003/2003H or Biol4003 or grad
BIOL 5272 - Applied Biostatistics
Credits: 4.0 [max 3.0]
Course Equivalencies: Biol 3272Biol 3272H//Biol 5272
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Conceptual basis of statistical analysis. Statistical analysis of biological data. Data visualization, descriptive statistics, significance tests, experimental design, linear model, simple/multiple regression, general linear model. Lectures, computer lab. prereq: High school algebra; BIOL 2003 recommended.
BMEN 5001 - Advanced Biomaterials
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Commonly used biomaterials. Chemical/physical aspects. Practical examples from such areas as cardiovascular/orthopedic applications, drug delivery, and cell encapsulation. Methods used for chemical analysis and for physical characterization of biomaterials. Effect of additives, stabilizers, processing conditions, and sterilization methods. prereq: 3301 or MatS 3011 or grad student or instr consent
BMEN 5041 - Tissue Engineering
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Fundamentals of wound healing and tissue repair; characterization of cell-matrix interactions; case study of engineered tissues, including skin, bone marrow, liver, vessel, and cartilage; regulation of biomaterials and engineered tissues. prereq: CSE upper div or grad student or med student or instr consent
BMEN 5101 - Advanced Bioelectricity and Instrumentation
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Instrumentation, computer systems, and processing requirements for clinical physiological signals. Electrode characteristics, signal processing, and interpretation of physiological events by ECG, EEG, and EMG. Measurement of respiration and blood volume/flow. prereq: [CSE upper div, grad student] or instructor consent
BMEN 5111 - Biomedical Ultrasound
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Introduction to biomedical ultrasound, including physics of ultrasound, transducer technology, medical ultrasound imaging, photoacoustic imaging, applications of non-linear acoustics, and high-intensity ultrasound. prereq: [[PHYS 1302 or equiv], [MATH 2374 or equiv]] or instr consent
BMEN 5151 - Introduction to BioMEMS and Medical Microdevices
Credits: 2.0 [max 2.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Design/microfabrication of sensors, actuators, drug delivery systems, microfluidic devices, and DNA/protein microarrays. Packaging, biocompatibility, ISO 10993 standards. Applications in medicine, research, and homeland security. prereq: CSE sr or grad student or medical student
BMEN 5201 - Advanced Biomechanics
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Introduction to biomechanics of musculoskeletal system. Anatomy, tissue material properties. Kinematics, dynamics, and control of joint/limb movement. Analysis of forces/motions within joints. Application to injury, disease. Treatment of specific joints, design of orthopedic devices/implants. prereq: [[3001 or equiv], [CSE upper div or grad student]] or instr consent
BMEN 5311 - Advanced Biomedical Transport Processes
Credits: 3.0 [max 3.0]
Course Equivalencies: BMEn 5311/ChEn 5753/ME 5381
Typically offered: Every Spring
Fluid flow and mass transfer in the body, bioreactors, and medical devices. Pulsatile flows. Flows around curved and deformable vessels. Boundary layer flows. Blood rheology. Interstitial (porous media) flows. Oxygenation. Cell migration. Student critiques of published papers.
BMEN 5321 - Microfluidics in Biology and Medicine
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Fundamentals of microfluidics. Fluid mechanics/transport phenomena in microscale systems. Pressure/surface driven flows. Capillary forces, electrokinetics, hydraulic circuit analysis. Finite element modeling for microfluidic systems. Design/fabrication methods for microfluidic devices. prereq: [3111, AEM 4201, ChEn 4005, [ME 3331 or ME 3332 or CSE grad student or instr consent]
BMEN 5351 - Cell Engineering
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Engineering approaches to cell-related phenomena important to cell/tissue engineering. Receptor/ligand binding. Trafficking/signaling processes. Applications to cell proliferation, adhesion, and motility. Cell-matrix interactions. prereq: [2401, [2501 or concurrent registration is required (or allowed) in 5501], [MATH 2243 or MATH 2373]] or CSE upper div or grad student or instr consent
BMEN 5401 - Advanced Biomedical Imaging
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Functional biomedical imaging modalities. Principles/applications of technologies that offer high spatial/temporal resolution. Bioelectromagnetic and magnetic resonance imaging. Other modalities. prereq: CSE upper div or grad student or instr consent
BMEN 5411 - Neural Engineering
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Theoretical basis. Signal processing techniques. Modeling of nervous system, its response to stimulation. Electrode design, neural modeling, cochlear implants, deep brain stimulation. Prosthetic limbs, micturition control, prosthetic vision. Brain machine interface, seizure prediction, optical imaging of nervous system, place cell recordings in hippocampus. prereq: 3401 recommended
BMEN 5412 - Neuromodulation
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Fundamentals of bioengineering approaches to modulate the nervous system, including bioelectricity, biomagnetism, and optogenetics. Computational modeling, design, and physiological mechanisms of neuromodulation technologies. Clinical exposure to managing neurological disorders with neuromodulation technology.
BMEN 5413 - Neural Decoding and Interfacing
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Neural interface technologies currently in use in patients as well as the biophysical, neural coding, and hardware features relating to their implementation in humans. Practical and ethical considerations for implanting these devices into humans. prereq: CSE upper division student, CSE graduate student, or instructor approval. recommended: BMEn 3411
BMEN 5421 - Introduction to Biomedical Optics
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Spring
Biomedical optical imaging/sensing principles, laser-tissue interaction, detector design, noise analysis, interferometry, spectroscopy. Optical coherence tomography, polarization, birefringence, flow measurement, fluorescence, nonlinear microscopy. Tours of labs. prereq: CSE sr or grad student
BMEN 5501 - Biology for Biomedical Engineers
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Concepts of cell/tissue structure/function. Basic principles of cell biology. Tissue engineering, artificial organs. prereq: Engineering upper div or grad student
BMEN 5701 - Cancer Bioengineering
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Cancer-specific cell, molecular/genetics events. Quantitative applications of bioinformatics/systems biology, optical imaging, cell/matrix mechanics. Drug transport (with some examination of design of novel therapeutics). prereq: [Upper division CSE undergraduate, CSE graduate student] or instr consent
BMEN 8001 - Polymeric Biomaterials
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Introduction to polymeric biomaterial research. Molecular engineering, characterization of properties, material-cell interaction, biocompatibility/bioactivity. Applications in biology and medicine. prereq: [5001, [CHEN 4214 or MATS 4214 or equiv]] or instr consent
BMEN 8041 - Advanced Tissue Engineering Lab
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Tissue engineering refers to the generation of biological substitutes to restore, maintain or improve tissue function. Toward this end, tools and knowledge from several disciplines might be applied including biological sciences (molecular, cellular and tissue anatomy and physiology), engineering (transport phenomena, material science, mechanical characterization) and biotechnology (cell culture, gene transfer, metabolomics). This course will cover some introductory and advanced lab techniques used in tissue engineering.
BMEN 8101 - Biomedical Digital Signal Processing
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Signal processing theory for analyzing real world digital signals. Digital signal processing and mathematically derived algorithms for analysis of stochastic signals. Spectral analyses, noise cancellation, optimal filtering, blind source separation, beamforming techniques. prereq: [[MATH 2243 or MATH 2373], [MATH 2263 or MATH 2374]] or equiv
BMEN 8201 - Advanced Tissue Mechanics
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Tissues exist in dynamic mechanical environments where they must maintain a fine balance between applied loads and internal tension. Active adaptability of biological materials can significantly complicate measurement of their mechanical behavior. This course will cover fundamental continuum approaches for determining the complex stress states of actively responsive tissues as well as the force-feedback relationships that drive early development and allow mature tissues to maintain mechanical equilibrium. Topics will include theoretical approaches for active force generation, soft tissue finite growth, extracellular matrix remodeling, and constrained mixtures. These methods are applicable to a wide range of biomechanical systems. In this course, they will be applied to mechanics of two model systems: arterial growth and remodeling in hypertension and sheet folding in early organogenesis and morphogenesis. prereq: 3011 or AEM 2021 or equiv
BMEN 8381 - Bioheat and Mass Transfer
Credits: 3.0 [max 3.0]
Course Equivalencies: BMEn 8381/ME 8381
Typically offered: Periodic Spring
Analytical/numerical tools to analyze heat/mass transfer phenomenon in cryobiological, hyperthermic, other biomedically relevant applications. prereq: CSE grad student, upper div transport/fluids course; [physics, biology] recommended
BMEN 8401 - New Product Design and Business Development
Credits: 4.0 [max 4.0]
Course Equivalencies: BMEn 8401/Entr 6041/PDes 8221
Prerequisites: BME graduate student, some design experience; 8401, 8402 must be taken same yr
Grading Basis: A-F or Aud
Typically offered: Every Fall
Student teams work with CSE and CSOM faculty and company representatives to develop a product concept for sponsoring company. Assignments include concept/detail design, manufacturing, marketing, introduction strategy, profit forecasting, production of product prototype. prereq: BME graduate student, some design experience; 8401, 8402 must be taken same yr
BMEN 8402 - New Product Design and Business Development
Credits: 4.0 [max 4.0]
Course Equivalencies: BMEn 8402/Entr 6087/PDes 8722
Prerequisites: 8401
Grading Basis: A-F or Aud
Typically offered: Every Spring
Student teams work with CSE and CSOM faculty and company representatives to develop a product concept for sponsoring company. Assignments include concept/detail design, manufacturing, marketing, introduction strategy, profit forecasting, production of product prototype. prereq: 8401
BMEN 8421 - Biophotonics
Credits: 3.0 [max 3.0]
Prerequisites: Graduate students in physical sciences (engineering, physics, chemistry etc.), or graduate students with an undergraduate degree in the physical sciences or mathematics, or consent of instructor. In addition to previous course work in engineering and/or physics, a working understanding of microscopy is recommended. Although not required, concurrent or previous enrollment in BMEn 5421 (Biomedical Optics) is recommended.
Grading Basis: A-F or Aud
Typically offered: Every Spring
Understanding light microscopy and the interaction of light with biological materials is widely applicable to numerous research programs. In fact, it is a fundamental approach to addressing critical questions at the cellular and subcellular scales. This course will emphasize the fundamentals of light microscopy and microscopes, fundamentals of fluorescence and fluorescence microscopy (transitions, quantum yield, bleaching, lifetime etc.) and practical applications of fluorescence microscopy (confocal microscopy for optical sectioning, multiphoton microscopy, harmonic generation, FRET, FRAP, and fluorescence lifetime in the time and frequency domains). Course material will span theory, practical applications of microscopy and published literature. prereq: Graduate students in physical sciences (engineering, physics, chemistry etc.), or graduate students with an undergraduate degree in the physical sciences or mathematics, or consent of instructor. In addition to previous course work in engineering and/or physics, a working understanding of microscopy is recommended. Although not required, concurrent or previous enrollment in BMEn 5421 (Biomedical Optics) is recommended.
BMEN 8501 - Dynamical Systems in Biology
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Nonlinear dynamics with specific emphasis on behavior of excitable systems (neurons/cardiac myocytes). prereq: Grad student in engineering or physics or math or physiology or neuroscience
BMEN 8502 - Physiological Control Systems
Credits: 3.0 [max 3.0]
Prerequisites: 8101 or equiv
Grading Basis: A-F only
Typically offered: Every Spring
Simulation, identification, and optimization of physiological control systems. Linear and non-linear systems analysis, stability analysis, system identification, and control design strategies, including constrained, adaptive, and intelligent control. Analysis and control of physiological system dynamics in normal and diseased states. prereq: 8101 or equiv
BMEN 8511 - Systems and Synthetic Biology
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Systems/synthetic biology methods used to characterize/engineer biological systems at molecular/cellular scales. Integration of quantitative experimental approaches/mathematical modeling to elucidate biological design principles, create new molecular/cellular functions.
BMEN 8900 - Special Topics in Biomedical Engineering
Credits: 1.0 -4.0 [max 8.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall & Spring
Topics in biomedical engineering.
CEGE 5211 - Highway Design & Traffic Operations
Credits: 4.0 [max 4.0]
Course Equivalencies: CEGE 4211/CEGE 5211
Grading Basis: A-F or Aud
Typically offered: Every Fall
Principles of vehicle/driver performance as they apply to design and operation of highways. Highway alignment and roadside design. Intersection design and traffic control devices. Capacity/level of service. Trip generation and traffic impact analysis. Safety studies and safety impacts of design and operational decisions. prereq: CEGE 3201, CEGE 3102 or equivalent, Grad Student
CEGE 5411 - Applied Structural Mechanics
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Principal Stresses and strain analysis; failure criteria. Introduction to plane elasticity, energymethods, torsion of beams, and bending of unsymmetrical beams. Introduction to structural dynamics and stability. prereq: AEM 3031, Upper div CSE or grad student or instr consent
CHEM 4001 - Chemistry of Biomass and Biomass Conversion to Fuels and Products (ENV)
Credits: 4.0 [max 4.0]
Course Equivalencies: BBE 4001/BBE 5001/Chem 4001
Grading Basis: A-F or Aud
Typically offered: Every Fall
Chemistry of biomass and its sustainable utilization for biofuels and bioproducts, including bio-based materials. Chemicals/energy and their environmental implications within the context of chemical principles and associated reactions underlying the structure, properties, processing, and performance of plant materials. prereq: Chem 2301 or Chem 1082 or instructor consent
CHEM 4011 - Mechanisms of Chemical Reactions
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Reaction mechanisms, methods of study. Mechanistic concepts. Gas phase reactions. "Electron pushing" mechanisms in organic/enzymatic reactions. Kinetic schemes, other strategies. prereq: [2302, 4501] or equiv
CHEM 4021 - Computational Chemistry
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Theoretical methods for study of molecular structure, bonding, and reactivity. Ab initio/semi-empirical calculations. Theoretical determination of molecular electronic structure/spectra, relation to experimental techniques. Molecular mechanics. Structure determination for large systems. Molecular properties/reactivity. Computational tools. Critical assessment of methods/theoretical work in the literature. Lab. prereq: [4502 or equiv], instr consent
CHEM 4101 - Modern Instrumental Methods of Chemical Analysis
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Basic electronic, optical, computer technologies in design of chemical instrumentation. Advanced topics in spectroscopy (e.g., FT-NMR, FT-IR, atomic absorption/emission). Electrochemistry. Mass spectrometry. prereq: 2101, 2111
CHEM 4111W - Modern Instrumental Methods of Chemical Analysis Lab (WI)
Credits: 2.0 [max 2.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Instrumental techniques, including spectroscopic methods, electrochemical methods, and analysis based on separation. Use of computers in data collection and reduction. prereq: 4101 or concurrent registration is required (or allowed)
CHEM 4201 - Materials Chemistry
Credits: 3.0 [max 3.0]
Course Equivalencies: Chem 4201/Chem 8201
Typically offered: Every Fall
Crystal systems/unit cells, phase diagrams, defects/interfaces, optical/dielectric properties, electrical/thermal conductivity, X-ray diffraction, thin film analysis, electronic structure, polarons/phonons, solid state chemistry, liquid/molecular crystals, polymers, magnetic/optical materials, porous materials, ceramics, piezoelectric materials, biomedical materials, catalysts. prereq: [[4502 or equiv], 4701] or instr consent
CHEM 4214 - Polymers
Credits: 3.0 [max 3.0]
Course Equivalencies: Chem 4214/ChEn 4214/MatS 4214
Grading Basis: A-F or Aud
Typically offered: Every Spring
Structure/morphology of crystalline/amorphous states. Crystallization kinetics. Vitrification, glass transition. Mechanical properties, failure, permeability, optical/electrical properties, polymer composites, effect of processing. prereq: [MATS 3011, [CHEN 3101 or CHEN 4101 or MATS 4001], [upper div MatS or ChEn or CHEM]] or instr consent
CHEM 4221 - Introduction to Polymer Chemistry
Credits: 3.0 [max 3.0]
Course Equivalencies: ChEn 8221/MatS 8221/Chem 8221
Typically offered: Every Fall
Condensation, radical, ionic, emulsion, ring-opening, metal-catalyzed polymerizations. Chain conformation, solution thermodynamics, molecular weight characterization, physical properties. prereq: [2302, 4501] or instr consent
CHEM 4223W - Polymer Laboratory (WI)
Credits: 2.0 [max 2.0]
Course Equivalencies: Chem 4223W/ChEn 4223/MatS4223W
Typically offered: Every Spring
Synthesis, characterization, and physical properties of polymers. Free radical, condensation, emulsion, anionic polymerization. Infrared spectroscopy/gel permeation chromatography. Viscoelasticity, rubber elasticity, crystallization. prereq: CHEM 4221 coreq CHEM 4214 or CHEN 4214 or MATS 4214 or instr consent
CHEM 4301 - Applied Surface and Colloid Science
Credits: 3.0 [max 3.0]
Course Equivalencies: BBE 4301/BBE 5301/Chem 4301
Typically offered: Every Fall
Introduction to surface/colloid science concepts. Surface tension, wetting, adsorption, capillarity. Formation/stability of sols, emulsions, and foams. Water solubility. Partition coefficients of organic species. Properties of both surfactants and water soluble polymers. Focuses on interdisciplinary applications. prereq: 3043 or BMEN 2101 or CHEN 3101 or CHEM 4501 or instr consent
CHEM 4311W - Advanced Organic Chemistry Lab (WI)
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Reactions, techniques, and instrumental methods in synthetic organic chemistry. prereq: 2311
CHEM 4321 - Organic Synthesis
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Fundamental concepts, reactions, reagents, structural/stereochemical issues, mechanistic skills for organic chemistry. prereq: [2302 or equiv], 4501, instr consent
CHEM 4322 - Advanced Organic Chemistry
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Topics vary by instructor. Examples: natural products, heterocycles, asymmetric synthesis, organometallic chemistry, polymer chemistry. prereq: [2302 or equiv], 4501, instr consent
CHEM 4352 - Physical Organic Chemistry
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Fundamental concepts and mechanistic tools for analysis of organic reaction mechanisms. Solvation, reactive intermediates, gas phase chemistry. Photochemistry/strained-ring chemistry. prereq: 4501, [4011 or 8011]
CHEM 4361 - Interpretation of Organic Spectra
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Application of nuclear magnetic resonance, mass, ultraviolet, and infrared spectral analyses to organic structural problems. prereq: [2302 or equiv], 4501, instr consent
CHEM 4411 - Introduction to Chemical Biology
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Chemistry of amino acids, peptides, proteins, lipids, carbohydrates, and nucleic acids. Structure, nomenclature, synthesis, reactivity. Techniques to characterize biomolecules. prereq: [2302 or 2081 equiv]
CHEM 4412 - Chemical Biology of Enzymes
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Enzyme classification with examples from current literature. Strategies to decipher enzyme mechanisms. Chemical approaches to control enzyme catalysis. prereq: [2302 or equiv], 4501
CHEM 4501 - Introduction to Thermodynamics, Kinetics, and Statistical Mechanics
Credits: 3.0 [max 3.0]
Course Equivalencies: Chem 3501/4501
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Physical chemistry as it relates to macroscopic descriptions of chemical systems. Chemical thermodynamics, phase equilibria, chemical equilibria. Statistical mechanics. Phenomenological reaction kinetics. Kinetic theory of gases. Collision, statistical theories of reaction rates. prereq: [1062/1066 or 1071H/1075H], [MATH 2263 or concurrent registration is required (or allowed) in MATH 2263 or MATH 2374 or concurrent registration is required (or allowed) in MATH 2374], [PHYS 1302 or PHYS 1402V or PHYS 1502V]
CHEM 4502 - Introduction to Quantum Mechanics and Spectroscopy
Credits: 3.0 [max 3.0]
Course Equivalencies: Chem 3502/4502
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Microscopic descriptions of chemical systems. Quantum theory. Applications to atomic/molecular structure. Molecular spectroscopy. Quantum statistical mechanics. Discussion of solutions to several differential equations. prereq: [1062/1066 or 1072H/1076H of 1082/1086], [MATH 2263 or concurrent registration is required (or allowed) in MATH 2263 or MATH 2374 or concurrent registration is required (or allowed) in MATH 2374 or MATH 2243 or concurrent registration is required (or allowed) in MATH 2243 or MATH 2373 or concurrent registration is required (or allowed) in MATH 2373], [PHYS 1302 or PHYS 1402V or PHYS 1502V]
CHEM 4511W - Advanced Physical Chemistry Lab (WI)
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Experiments illustrating principles and methods of thermodynamics, reaction kinetics, and quantum mechanics. prereq: 4502, chemistry major
CHEM 4601 - Green Chemistry (ENV)
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Survey key aspects of green chemistry in modern research and development both in academia and industry, as well as relevant implications for the environment, technology, and public policy. prereq: [2302 or 2081 or equiv]
CHEM 4701 - Inorganic Chemistry
Credits: 3.0 [max 3.0]
Course Equivalencies: Chem 4701 / Chem 4701H
Typically offered: Every Fall & Spring
Periodic trends. Structure/bonding in compounds where s and p electrons are important. Descriptive chemistry of solids and transition metal compounds. Transition metal chemistry. Topics in main group and materials chemistry. prereq: [2311 or concurrent registration is required (or allowed) in 2311], [4501 or concurrent registration is required (or allowed) in 4501 or 4502 or concurrent registration is required (or allowed) in 4502]
CHEM 4711W - Advanced Inorganic Chemistry Lab (WI)
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Lab experiments in inorganic/organometallic chemistry illustrating synthetic/spectroscopic techniques. prereq: 4701, chem major
CHEM 4715 - Physical Inorganic Chemistry
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Physical methods (e.g., IR, UV-VIS, ESR, Mossbauer and mass spectroscopy, magnetic measurements, X-ray diffraction) and concepts applied to inorganic and organometallic systems. prereq: 4701 or equiv, chem major or instr consent
CHEM 4725 - Organometallic Chemistry
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall
Synthesis, reactions, structures, and other properties of main group and transition metal organometallic compounds; electronic and structural theory, emphasizing their use as stoichiometric and homogeneous catalytic reagents in organic and inorganic systems. prereq: 4701 or equiv, chem major or instr consent
CHEM 4735 - Bioinorganic Chemistry
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Role of metal ions in biology. Emphasizes structure, function, and spectroscopy of metalloproteins and their synthetic analogs. prereq: 4701 or equiv, chem grad or instr consent
CHEM 4745 - Advanced Inorganic Chemistry
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Topics in main group and transition metal chemistry. Emphasizes synthesis, structure, physical properties, and chemical reactivity. prereq: 4701, chem major, instr consent
CHEM 5755 - X-Ray Crystallography
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Essentials of crystallography as applied to modern, single crystal X-ray diffraction methods. Practical training in use of instrumentation in X-ray crystallography facility in Department of Chemistry. Date collection, correction/refinement, structure solutions, generation of publication materials, use of Cambridge Crystallographic Structure Database. prereq: Chem grad student or instr consent
CHEM 8152 - Analytical Spectroscopy
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Survey of analytical spectroscopic methods. Design/application of spectroscopic instruments, including signal generation, acquisition, and interpretation. May include nuclear magnetic resonance, electron paramagnetic resonance, infrared and ultraviolet/visible spectroscopy, and mass spectrometry. prereq: grad chem major or instr consent
CHEM 8201 - Materials Chemistry
Credits: 4.0 [max 4.0]
Course Equivalencies: Chem 4201/Chem 8201
Grading Basis: A-F or Aud
Typically offered: Every Fall
Crystal systems/unit cells, phase diagrams, defects/interfaces, optical/ dielectric properties, electrical/thermal conductivity, X-ray diffraction, thin film analysis, electronic structure, polarons/phonons, solid state chemistry, liquid/molecular crystals, polymers, magnetic/optical materials, porous materials, ceramics, piezoelectric materials, biomedical materials, catalysts. prereq: [4701, 3502] or instr consent
CHEM 8551 - Quantum Mechanics I
Credits: 4.0 [max 4.0]
Course Equivalencies: Chem 5551/8551
Typically offered: Every Fall
Review of classical mechanics. Postulates of quantum mechanics with applications to determination of single particle bound state energies and scattering cross-sections in central field potentials. Density operator formalism with applications to description of two level systems, two particle systems, entanglement, and Bell inequality. prereq: undergrad physical chem course
CHEM 8552 - Quantum Mechanics II
Credits: 2.0 [max 4.0]
Typically offered: Every Spring
Second Quantization;Density matrices; Molecular Electronic Structure Theory; Hartree-Fock Theory; Electron Correlation; Configuration Interaction; Perturbation Theory; Energy Derivatives; Coupled-Cluster;Density Functional Theory; Relativistic Quantum Chemistry; prereq: 8551
CHEN 4214 - Polymers
Credits: 3.0 [max 3.0]
Course Equivalencies: Chem 4214/ChEn 4214/MatS 4214
Grading Basis: A-F or Aud
Typically offered: Every Spring
Polymer structure-property relations: structure/morphology of crystalline/amorphous states. Crystallization kinetics. Vitrification and the glass transition. Mechanical properties, failure, permeability, optical/electrical properties, polymer composites, effect of processing on properties. prereq: [[MATS 3011, [3101 or MATS 3001], [upper div MatS or ChEn]]] or instr consent
CHEN 4401W - Senior Chemical Engineering Lab (WI)
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Fall
Principles/techniques of efficient design, structure, measurement, planning, analysis, presentation of experiments. Energy balances, fluid flow, heat transfer, mass transfer. Design of new systems using experimental data obtained in lab. Oral/written presentations. prereq: CHEN 3006, CHEN 3401W
CHEN 4501W - Chemical Engineering Design (WI)
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Spring
Engineering economics of process evaluation, including time/bases for cost estimation. Engineering design through group projects. Case studies. prereq: CHEN 3401W, ChEn 3102, ChEn 3006 (or &3006), Chem 2301
CHEN 4601 - Process Control
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Analysis of dynamic behavior/design of linear control systems for chemical processes. Dynamic response/stability of linear ODE systems, tuning of PID controllers, synthesis of feedback, feedforward/feedback controller. prereq: [3102 or 4102], [upper div ChEn major or dept consent], C- or better in all pre-reqs
CHEN 4701 - Applied Math
Credits: 3.0 [max 3.0]
Course Equivalencies: ChEn 4701/ChEn 8201
Grading Basis: A-F only
Typically offered: Every Fall
Integrated approach to solving linear mathematical problems (linear algebraic equations, linear ordinary/partial differential equations) using theoretical/numerical analysis based on linear operator theory. Undergraduate version of 8201. prereq: [3102 or 4102], ChEn major upper div
CHEN 4702 - Introduction to Rheology
Credits: 2.0 [max 2.0]
Grading Basis: A-F only
Typically offered: Every Fall
Deformation/flow of non-Newtonian/viscoelastic fluids, plastic materials, perfectly elastic solids. Phenomenological/molecular interpretation of rheology of elastomers, polymer melts, polymer solutions. Application of rheology to polymer processing. prereq: [3005 or 4005], instr consent
CHEN 4704 - Advanced Undergraduate Physical Rate Processes I: Transport
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Mass transfer, dilute/concentrated diffusion, Brownian motion. Diffusion coefficients in polymers, of electrolytes, at critical points. Multicomponent diffusion. Correlations/predictions. Mass transfer, chemical reaction. prereq: [3005 or 4005], ChEn major upper div
CHEN 4708 - Advanced Undergraduate Chemical Rate Processes: Analysis of Chemical Reactors
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Spring
Design of reactors for heat management, with catalytic processes. Analysis of steady state, transient behavior. Polymerization, combustion, solids processing, environmental modeling. Design of multiphase reactors. prereq: [3102 or 4102], ChEn major upper div
CHEN 5751 - Biochemical Engineering
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Chemical engineering principles applied to analysis/design of complex cellular/enzyme processes. Quantitative framework for design of cells for production of proteins, synthesis of antibodies with mammalian cells, or degradation of toxic compounds in contaminated soil. prereq: [3005 or 4005], [concurrent registration is required (or allowed) in 3006 or concurrent registration is required (or allowed) in 4006], [concurrent registration is required (or allowed) in 3102 or concurrent registration is required (or allowed) in 4102]
CHEN 5753 - Advanced Biomedical Transport Processes
Credits: 3.0 [max 3.0]
Course Equivalencies: BMEn 5311/ChEn 5753/ME 5381
Grading Basis: A-F or Aud
Typically offered: Every Spring
Fluid, mass, heat transport in biological systems. Mass transfer across membranes, fluid flow in capillaries, interstitium, veins, and arteries Heat transfer in single cells/tissues. Whole organ, body heat transfer issues. Blood flow, oxygenation. Heat/mass transfer in respiratory systems. Biotransport issues in artificial organs, membrane oxygenators, drug delivery applications. prereq: 3005 or 4005 or equiv
CHEN 5771 - Colloids and Dispersions
Credits: 3.0 [max 3.0]
Course Equivalencies: ChEn 5771/MatS 5771
Grading Basis: A-F or Aud
Typically offered: Every Fall
Preparation, stability, coagulation kinetics or colloidal solutions. DLVO theory, electrokinetic phenomena. Properties of micelles, other microstructures. prereq: Physical chemistry
CHEN 8101 - Fluid Mechanics
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Equations of change of mass, momentum, angular momentum. Kinematics of deformation, convective transport. Applications to fluid statics/dynamics of Newtonian fluids. Examples of exact solutions of Navier-Stokes equations, useful simplifications. prereq: Chemical engineering grad student or instr consent
CHEN 8401 - Physical and Chemical Thermodynamics
Credits: 3.0 [max 3.0]
Course Equivalencies: ChEn 4706/ChEn 8401
Grading Basis: A-F or Aud
Typically offered: Every Fall
Principles of thermodynamics with emphasis on solving problems encountered in chemical engineering and materials science. An organized exposition of fundamental concepts that will help students understand and analyze the systems they are likely to encounter while conducting original research. This course is for students who seek a much deeper understanding than a typical undergraduate course provides. prereq: Undergraduate engineering course or chemistry course in thermodynamics, Chemical Engineering graduate student, or instructor consent.
CHEN 8754 - Systems Analysis of Biological Processes
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Relating biological processes at molecular level to physiological level of cells/organisms/populations. Methodology for analyzing data. Quantification of molecular interplays. prereq: Grad student in [life sciences or chemical/physical sciences or engineering]; ChEn students must take A/F
CMB 5200 - Statistical Genetics and Genomics
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Fall Even Year
Statistical issues in genomics. Gene detection, including statistical analysis/designs for linkage study and for mapping quantitative trait loci. Linkage analysis using pedigree data for codominant/dominant markers. Using radiation hybrid mapping and single cell typing. Design issues in linkage analysis, parentage testing, and marker polymorphism.
CSCI 4011 - Formal Languages and Automata Theory
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Logical/mathematical foundations of computer science. Formal languages, their correspondence to machine models. Lexical analysis, string matching, parsing. Decidability, undecidability, limits of computability. Computational complexity. prereq: 2041 or instr consent
CSCI 4041 - Algorithms and Data Structures
Credits: 4.0 [max 4.0]
Course Equivalencies: CSci 4041/CSci 4041H
Typically offered: Every Fall & Spring
Rigorous analysis of algorithms/implementation. Algorithm analysis, sorting algorithms, binary trees, heaps, priority queues, heapsort, balanced binary search trees, AVL trees, hash tables and hashing, graphs, graph traversal, single source shortest path, minimum cost spanning trees. prereq: [(1913 or 1933) and 2011] or instr consent; cannot be taken for grad CSci cr
CSCI 4061 - Introduction to Operating Systems
Credits: 4.0 [max 4.0]
Course Equivalencies: CSci 4061/INet 4001
Typically offered: Every Fall & Spring
Processes/threads, process coordination, interprocess communication, asynchronous events, memory management/file systems. Systems programming projects using operating system interfaces and program development tools. prereq: 2021 or EE 2361; CS upper div, CompE upper div., EE upper div., EE grad, ITI upper div., Univ. honors student, or dept. permission; no cr for grads in CSci.
CSCI 4131 - Internet Programming
Credits: 3.0 [max 3.0]
Course Equivalencies: CSci 4131/CSci 5131
Typically offered: Every Fall & Spring
Issues in internet programming. Internet history, architecture/protocols, network programming, Web architecture. Client-server architectures and protocols. Client-side programming, server-side programming, dynamic HTML, Java programming, object-oriented architecture/design, distributed object computing, Web applications. prereq: 4061, 4211 recommended, cannot be taken for grad CSci cr
CSCI 4211 - Introduction to Computer Networks
Credits: 3.0 [max 3.0]
Course Equivalencies: CSci 4211/CSci 5211/INET 4002
Typically offered: Every Fall & Spring
Concepts, principles, protocols, and applications of computer networks. Layered network architectures, data link protocols, local area networks, routing, transport, network programming interfaces, networked applications. Examples from Ethernet, Token Ring, TCP/IP, HTTP, WWW. prereq: 4061 or instr consent; basic knowledge of [computer architecture, operating systems] recommended, cannot be taken for grad CSci cr
CSCI 4511W - Introduction to Artificial Intelligence (WI)
Credits: 4.0 [max 4.0]
Course Equivalencies: CSci 4511W/CSci 5511
Typically offered: Every Fall & Spring
Problem solving, search, inference techniques. Knowledge representation. Planning. Machine learning. Robotics. Lisp programming language. Cannot be taken for grad CSci credit. prereq: 2041 or instr consent
CSCI 4611 - Programming Interactive Computer Graphics and Games
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Tools/techniques for programming games/interactive computer graphics. Event loops, rendering/animation, polygonal models, texturing, physical simulation. Modern graphics toolkits. History/future of computer games technology. Social impact of interactive computer graphics. prereq: 2021 or instr consent
CSCI 4707 - Practice of Database Systems
Credits: 3.0 [max 3.0]
Course Equivalencies: CSci 4707/CSci 5707/INET 4707
Typically offered: Every Fall & Spring
Concepts, conceptual data models, case studies, common data manipulation languages, logical data models, database design, facilities for database security/integrity, applications. prereq: 4041 or instr consent
CSCI 4921 - History of Computing (TS, HIS)
Credits: 3.0 [max 3.0]
Course Equivalencies: CSci 4921/HSci 4321
Typically offered: Fall Even Year
Developments in last 150 years; evolution of hardware and software; growth of computer and semiconductor industries and their relation to other businesses; changing relationships resulting from new data-gathering and analysis techniques; automation; social and ethical issues.
CSCI 4970W - Advanced Project Laboratory (WI)
Credits: 3.0 [max 9.0]
Typically offered: Every Fall & Spring
Formulate and solve open-ended project: design, implement, interface, document, test. Team work strongly encouraged. Arranged with CSci faculty. prereq: Upper div CSci, 4061, instr consent; cannot be taken for grad cr
CSCI 5103 - Operating Systems
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Conceptual foundation of operating system designs and implementations. Relationships between operating system structures and machine architectures. UNIX implementation mechanisms as examples. prereq: 4061 or instr consent
CSCI 5105 - Introduction to Distributed Systems
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Distributed system design and implementation. Distributed communication and synchronization, data replication and consistency, distributed file systems, fault tolerance, and distributed scheduling. prereq: [5103 or equiv] or instr consent
CSCI 5106 - Programming Languages
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Design and implementation of high-level languages. Course has two parts: (1) language design principles, concepts, constructs; (2) language paradigms, applications. Note: course does not teach how to program in specific languages. prereq: 4011 or instr consent
CSCI 5115 - User Interface Design, Implementation and Evaluation
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Theory, design, programming, and evaluation of interactive application interfaces. Human capabilities and limitations, interface design and engineering, prototyping and interface construction, interface evaluation, and topics such as data visualization and World Wide Web. Course is built around a group project. prereq: 4041 or instr consent
CSCI 5125 - Collaborative and Social Computing
Credits: 3.0 [max 3.0]
Typically offered: Spring Even Year
Introduction to computer-supported cooperative work, social computing. Technology, research methods, theory, case studies of group computing systems. Readings, hands-on experience. prereq: 5115 or instr consent
CSCI 5143 - Real-Time and Embedded Systems
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Periodic Spring
Real-time systems that require timely response by computer to external stimulus. Embedded systems in which computer is part of machine. Increasing importance of these systems in commercial products. How to control robots and video game consoles. Lecture, informal lab. prereq: [4061 or instr consent], experience with C language
CSCI 5161 - Introduction to Compilers
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Techniques for translating modern programming languages to intermediate forms or machine-executable instructions/their organization into compiler. Lexical analysis, syntax analysis, semantic analysis, data flow analysis, code generation. Compiler project for prototypical language. prereq: [2021, 5106] or instr consent
CSCI 5211 - Data Communications and Computer Networks
Credits: 3.0 [max 3.0]
Course Equivalencies: CSci 4211/CSci 5211/INET 4002
Typically offered: Every Fall
Concepts, principles, protocols, and applications of computer networks. Layered network architectures, data link protocols, local area networks, network layer/routing protocols, transport, congestion/flow control, emerging high-speed networks, network programming interfaces, networked applications. Case studies using Ethernet, Token Ring, FDDI, TCP/IP, ATM, Email, HTTP, and WWW. prereq: [4061 or instr consent], basic knowledge of [computer architecture, operating systems, probability], grad student
CSCI 5221 - Foundations of Advanced Networking
Credits: 3.0 [max 3.0]
Typically offered: Spring Even Year
Design principles, protocol mechanisms. Network algorithmics, implementation techniques. Advanced network architectures, state-of-art/emerging networking technologies/applications, network modeling. Simulation, experiments. prereq: 4211 or 5211 or equiv; intro course in computer networks recommended
CSCI 5271 - Introduction to Computer Security
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Concepts of computer, network, and information security. Risk analysis, authentication, access control, security evaluation, audit trails, cryptography, network/database/application security, viruses, firewalls. prereq: 4061 or 5103 or equiv or instr consent
CSCI 5302 - Analysis of Numerical Algorithms
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Additional topics in numerical analysis. Interpolation, approximation, extrapolation, numerical integration/differentiation, numerical solutions of ordinary differential equations. Introduction to optimization techniques. prereq: 2031 or 2033 or instr consent
CSCI 5304 - Computational Aspects of Matrix Theory
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Perturbation theory for linear systems and eigenvalue problems. Direct/iterative solution of large linear systems. Matrix factorizations. Computation of eigenvalues/eigenvectors. Singular value decomposition. LAPACK/other software packages. Introduction to sparse matrix methods. prereq: 2031 or 2033 or instr consent
CSCI 5421 - Advanced Algorithms and Data Structures
Credits: 3.0 [max 3.0]
Typically offered: Every Fall & Spring
Fundamental paradigms of algorithm and data structure design. Divide-and-conquer, dynamic programming, greedy method, graph algorithms, amortization, priority queues and variants, search structures, disjoint-set structures. Theoretical underpinnings. Examples from various problem domains. prereq: 4041 or instr consent
CSCI 5451 - Introduction to Parallel Computing: Architectures, Algorithms, and Programming
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Parallel architectures design, embeddings, routing. Examples of parallel computers. Fundamental communication operations. Performance metrics. Parallel algorithms for sorting. Matrix problems, graph problems, dynamic load balancing, types of parallelisms. Parallel programming paradigms. Message passing programming in MPI. Shared-address space programming in openMP or threads. prereq: 4041 or instr consent
CSCI 5461 - Functional Genomics, Systems Biology, and Bioinformatics
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Computational methods for analyzing, integrating, and deriving predictions from genomic/proteomic data. Analyzing gene expression, proteomic data, and protein-protein interaction networks. Protein/gene function prediction, Integrating diverse data, visualizing genomic datasets. prereq: 3003 or 4041 or instr consent
CSCI 5471 - Modern Cryptography
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Introduction to cryptography. Theoretical foundations, practical applications. Threats, attacks, and countermeasures, including cryptosystems and cryptographic protocols. Secure systems/networks. History of cryptography, encryption (conventional, public key), digital signatures, hash functions, message authentication codes, identification, authentication, applications. prereq: [2011, 4041, [familiarity with number theory or finite fields]] or instr consent
CSCI 5481 - Computational Techniques for Genomics
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Techniques to analyze biological data generated by genome sequencing, proteomics, cell-wide measurements of gene expression changes. Algorithms for single/multiple sequence alignments/assembly. Search algorithms for sequence databases, phylogenetic tree construction algorithms. Algorithms for gene/promoter and protein structure prediction. Data mining for micro array expression analysis. Reverse engineering of regulatory networks. prereq: 4041 or instr consent
CSCI 5511 - Artificial Intelligence I
Credits: 3.0 [max 3.0]
Course Equivalencies: CSci 4511W/CSci 5511
Prerequisites: [2041 or #], grad student
Typically offered: Every Fall
Introduction to AI. Problem solving, search, inference techniques. Logic/theorem proving. Knowledge representation, rules, frames, semantic networks. Planning/scheduling. Lisp programming language. prereq: [2041 or instr consent], grad student
CSCI 5512 - Artificial Intelligence II
Credits: 3.0 [max 3.0]
Course Equivalencies: CSci 5512W/CSci 5512
Typically offered: Every Spring
Uncertainty in artificial intelligence. Probability as a model of uncertainty, methods for reasoning/learning under uncertainty, utility theory, decision-theoretic methods. prereq: [STAT 3021, 4041] or instr consent
CSCI 5521 - Machine Learning Fundamentals
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall
Problems of pattern recognition, feature selection, measurement techniques. Statistical decision theory, nonstatistical techniques. Automatic feature selection/data clustering. Syntactic pattern recognition. Mathematical pattern recognition/artificial intelligence. Prereq: [2031 or 2033], STAT 3021, and knowledge of partial derivatives
CSCI 5523 - Introduction to Data Mining
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Data pre-processing techniques, data types, similarity measures, data visualization/exploration. Predictive models (e.g., decision trees, SVM, Bayes, K-nearest neighbors, bagging, boosting). Model evaluation techniques, Clustering (hierarchical, partitional, density-based), association analysis, anomaly detection. Case studies from areas such as earth science, the Web, network intrusion, and genomics. Hands-on projects. prereq: 4041 or equiv or instr consent
CSCI 5525 - Machine Learning: Analysis and Methods
Credits: 3.0 [max 3.0]
Typically offered: Fall Even Year
Models of learning. Supervised algorithms such as perceptrons, logistic regression, and large margin methods (SVMs, boosting). Hypothesis evaluation. Learning theory. Online algorithms such as winnow and weighted majority. Unsupervised algorithms, dimensionality reduction, spectral methods. Graphical models. prereq: Grad student or instr consent
CSCI 5551 - Introduction to Intelligent Robotic Systems
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall
Transformations, kinematics/inverse kinematics, dynamics, control. Sensing (robot vision, force control, tactile sensing), applications of sensor-based robot control, robot programming, mobile robotics, microrobotics. prereq: 2031 or 2033 or instr consent
CSCI 5552 - Sensing and Estimation in Robotics
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Bayesian estimation, maximum likelihood estimation, Kalman filtering, particle filtering. Sensor modeling and fusion. Mobile robot motion estimation (odometry, inertial,laser scan matching, vision-based) and path planning. Map representations, landmark-based localization, Markov localization, simultaneous localization/mapping (SLAM), multi-robot localization/mapping. prereq: [5551, Stat 3021] or instr consent
CSCI 5561 - Computer Vision
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Issues in perspective transformations, edge detection, image filtering, image segmentation, and feature tracking. Complex problems in shape recovery, stereo, active vision, autonomous navigation, shadows, and physics-based vision. Applications. prereq: CSci 5511, 5521, or instructor consent.
CSCI 5607 - Fundamentals of Computer Graphics 1
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Fundamental algorithms in computer graphics. Emphasizes programming projects in C/C++. Scan conversion, hidden surface removal, geometrical transformations, projection, illumination/shading, parametric cubic curves, texture mapping, antialising, ray tracing. Developing graphics software, graphics research. prereq: concurrent registration is required (or allowed) in 2033, concurrent registration is required (or allowed) in 3081
CSCI 5608 - Fundamentals of Computer Graphics II
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Advanced topics in image synthesis, modeling, rendering. Image processing, image warping, global illumination, non-photorealistic rendering, texture synthesis. Parametric cubic surfaces, subdivision surfaces, acceleration techniques, advanced texture mapping. Programming in C/C++. prereq: 5607 or instr consent
CSCI 5609 - Visualization
Credits: 3.0 [max 3.0]
Typically offered: Fall Even Year
Fundamental theory/practice in data visualization. Programming applications. Perceptual issues in effective data representation, multivariate visualization, information visualization, vector field/volume visualization. prereq: [1913, 4041] or equiv or instr consent
CSCI 5611 - Animation & Planning in Games
Credits: 3.0 [max 3.0]
Typically offered: Fall Odd Year
Theory behind algorithms used to bring virtual worlds to life. Computer animation topics. Real-time, interactive techniques used in modern games. Physically-based animation, motion planning, character animation, simulation in virtual worlds. prereq: 4041 or 4611 or instr consent
CSCI 5619 - Virtual Reality and 3D Interaction
Credits: 3.0 [max 3.0]
Typically offered: Spring Odd Year
Introduction to software, technology/applications in virtual/augmented reality, 3D user interaction. Overview of current research. Hands-on projects. prereq: 4611 or 5607 or 5115 or equiv or instr consent
CSCI 5707 - Principles of Database Systems
Credits: 3.0 [max 3.0]
Course Equivalencies: CSci 4707/CSci 5707/INET 4707
Typically offered: Every Fall
Concepts, database architecture, alternative conceptual data models, foundations of data manipulation/analysis, logical data models, database designs, models of database security/integrity, current trends. prereq: [4041 or instr consent], grad student
CSCI 5708 - Architecture and Implementation of Database Management Systems
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Techniques in commercial/research-oriented database systems. Catalogs. Physical storage techniques. Query processing/optimization. Transaction management. Mechanisms for concurrency control, disaster recovery, distribution, security, integrity, extended data types, triggers, and rules. prereq: 4041 or 4707 or 5707 or instr. consent
CSCI 5801 - Software Engineering I
Credits: 3.0 [max 3.0]
Prerequisites: 2041 or #
Typically offered: Every Fall
Advanced introduction to software engineering. Software life cycle, development models, software requirements analysis, software design, coding, maintenance. prereq: 2041 or instr consent
CSCI 5802 - Software Engineering II
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Introduction to software testing, software maturity models, cost specification models, bug estimation, software reliability models, software complexity, quality control, and experience report. Student groups specify, design, implement, and test partial software systems. Application of general software development methods and principles from 5801. prereq: 5801 or instr consent
CSCI 8161 - Advanced Compiler Techniques
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Techniques for uniprocessors and parallel computers. Fundamental program analysis instruments such as data flow analysis and data dependence analysis. Variety of code generation and transformation techniques. prereq: 4061 or instr consent
CSCI 8211 - Advanced Computer Networks and Their Applications
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Current research issues in traffic and resource management, quality-of-service provisioning for integrated services networks (such as next-generation Internet and ATM networks) and multimedia networking. prereq: 5211 or instr consent
CSCI 8314 - Sparse Matrix Computations
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Sparsity and sparse matrices. Data structures for sparse matrices. Direct methods for sparse linear systems. Reordering techniques to reduce fill-in such as minimal degree ordering and nested dissection ordering. Iterative methods. Preconditioning algorithms. Algorithms for sparse eigenvalue problems and sparse least-squares. prereq: 5304 or numerical linear algebra course or instr consent
CSCI 8363 - Numerical Linear Algebra in Data Exploration
Credits: 3.0 [max 3.0]
Typically offered: Periodic Spring
Computational methods in linear algebra, matrix decompositions for linear equations, least squares, eigenvalue problems, singular value decomposition, conditioning, stability in method for machine learning, large data collections. Principal directions, unsupervised clustering, latent semantic indexing, linear least squares fit. Markov chain models on hyperlink structure. prereq: 5304 or instr consent
CSCI 8980 - Special Advanced Topics in Computer Science
Credits: 1.0 -3.0 [max 27.0]
Typically offered: Every Fall & Spring
Lectures and informal discussions. prereq: instr consent
ESCI 5201 - Time-Series Analysis of Geological Phenomena
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall
Time-series analysis of linear and nonlinear geological and geophysical phenomena. Examples drawn from ice age cycles, earthquakes, climatic fluctuations, volcanic eruptions, atmospheric phenomena, thermal convection and other time-dependent natural phenomena. Modern concepts of nonlinear dynamics and complexity theory applied to geological phenomena. prereq: Math 2263 or instr consent
ESCI 5204 - Geostatistics and Inverse Theory
Credits: 3.0 [max 3.0]
Typically offered: Fall Odd Year
Statistical treatment of geological and geophysical data. Statistical estimation. Stochastic processes/fields. Non-linear/non-assumptive error analysis. Cluster analysis. Eigenvalue-eigenvector methods. Regional variables. Correlograms and kriging. Theoretical framework of linear geostatistics and geophysical inverse theory. prereq: Stat 3011 or instr consent
ESCI 5302 - Isotope Geology
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Theory and uses of radioactive, radiogenic, and stable isotopes in geology. Radioactive dating, geothermometry, and tracer techniques in geologic processes. prereq: 3303W or instr consent
ESCI 5353 - Electron Microprobe Theory and Practice
Credits: 3.0 [max 3.0]
Course Equivalencies: ESci 5353/MatS 5353
Typically offered: Periodic Fall
Characterizing solid materials with electron beam instrumentation, including reduction of X-ray data to chemical compositions. prereq: [One yr chem, one yr physics] or instr consent
GCD 5036 - Molecular Cell Biology
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Analysis of dynamic cellular activities at the molecular level in cell biological fields that are experiencing new research advances not yet reflected in textbooks. Significant emphasis is placed on understanding the experimental basis of our current knowledge of cellular processes through analysis of scientific papers. Project and presentation-based assessments of learning outcomes. prereq: BIOL 4004 or GCD 4005W or grad
IE 5111 - Systems Engineering I
Credits: 2.0 [max 2.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Overview of systems-level thinking/techniques in context of an integrated, design-oriented framework. Elements of systems engineering process, including lifecycle, concurrent, and global engineering. Framework for engineering large-scale, complex systems. How specific techniques fit into framework. prereq: CSE upper div or grad student
IE 5113 - Systems Engineering II
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Systems engineering thinking/techniques presented in 5111. Hands-on techniques applied to specific problems. Topics pertinent to effectiveness of design process. Practices and organizational/reward structure to support collaborative, globally distributed design team.
IE 5441 - Financial Decision Making
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Fall, Spring & Summer
Cash flow streams, interest rates, fixed income securities. Evaluating investment alternatives, capital budgeting, dynamic cash flow process. Mean-variance portfolio selection, Capital Asset Pricing Model, utility maximization, risk aversion. Derivative securities, asset dynamics, basic option pricing theory. prereq: CSE upper div or grad student
IE 8531 - Discrete Optimization
Credits: 4.0 [max 8.0]
Typically offered: Periodic Fall & Spring
Topics in integer programming and combinatorial optimization. Formulation of models, branch-and-bound. Cutting plane and branch-and-cut algorithms. Polyhedral combinatorics. Heuristic approaches. Introduction to computational complexity.
IE 8532 - Stochastic Processes and Queuing Systems
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Introduction to stochastic modeling and processes. Random variables, discrete and continuous Markov chains, renewal processes, queuing systems, Brownian motion, and elements of reliability and stochastic simulation. Applications to design, planning, and control of manufacturing and production systems. prereq: 4521 or equiv
IE 8534 - Advanced Topics in Operations Research
Credits: 1.0 -4.0 [max 8.0]
Typically offered: Periodic Fall & Spring
Special topics determined by instructor. Examples include Markov decision processes, stochastic programming, integer/combinatorial optimization, and queueing networks.
MATH 4065 - Theory of Interest
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Time value of money, compound interest and general annuities, loans, bonds, general cash flows, basic financial derivatives and their valuation. Primarily for students who are interested in actuarial mathematics. prereq: 1272 or 1372 or 1572
MATH 4152 - Elementary Mathematical Logic
Credits: 3.0 [max 3.0]
Course Equivalencies: Math 4152/5165
Typically offered: Every Spring
Propositional logic. Predicate logic: notion of a first order language, a deductive system for first order logic, first order structures, Godel's completeness theorem, axiom systems, models of formal theories. prereq: one soph math course or instr consent
MATH 4242 - Applied Linear Algebra
Credits: 4.0 [max 4.0]
Course Equivalencies: Math 4242/Math 4457
Typically offered: Every Fall, Spring & Summer
Systems of linear equations, vector spaces, subspaces, bases, linear transformations, matrices, determinants, eigenvalues, canonical forms, quadratic forms, applications. prereq: 2243 or 2373 or 2573
MATH 4281 - Introduction to Modern Algebra
Credits: 4.0 [max 4.0]
Typically offered: Periodic Fall
Equivalence relations, greatest common divisor, prime decomposition, modular arithmetic, groups, rings, fields, Chinese remainder theorem, matrices over commutative rings, polynomials over fields. prereq: 2283 or 3283 or instr consent
MATH 4428 - Mathematical Modeling
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Modeling techniques for analysis/decision-making in industry. Optimization (sensitivity analysis, Lagrange multipliers, linear programming). Dynamical modeling (steady-states, stability analysis, eigenvalue methods, phase portraits, simulation). Probabilistic methods (probability/statistical models, Markov chains, linear regression, simulation). prereq: 2243 or 2373 or 2573
MATH 4512 - Differential Equations with Applications
Credits: 3.0 [max 3.0]
Typically offered: Every Fall & Spring
Laplace transforms, series solutions, systems, numerical methods, plane autonomous systems, stability. prereq: 2243 or 2373 or 2573
MATH 4567 - Applied Fourier Analysis
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Fourier series, integral/transform. Convergence. Fourier series, transform in complex form. Solution of wave, heat, Laplace equations by separation of variables. Sturm-Liouville systems, finite Fourier, fast Fourier transform. Applications. Other topics as time permits. prereq: 2243 or 2373 or 2573
MATH 4603 - Advanced Calculus I
Credits: 4.0 [max 4.0]
Course Equivalencies: Math 4606/Math 5615/Math 5616
Typically offered: Every Fall, Spring & Summer
Axioms for the real numbers. Techniques of proof for limits, continuity, uniform convergence. Rigorous treatment of differential/integral calculus for single-variable functions. prereq: [[2243 or 2373], [2263 or 2374]] or 2574 or instr consent
MATH 4604 - Advanced Calculus II
Credits: 4.0 [max 4.0]
Course Equivalencies: Math 4604/Math 5616
Typically offered: Every Spring
Sequel to MATH 4603. Topology of n-dimensional Euclidean space. Rigorous treatment of multivariable differentiation and integration, including chain rule, Taylor's Theorem, implicit function theorem, Fubini's Theorem, change of variables, Stokes' Theorem. prereq: 4603 or 5615 or instr consent
MATH 4653 - Elementary Probability
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Probability spaces, distributions of discrete/continuous random variables, conditioning. Basic theorems, calculational methodology. Examples of random sequences. Emphasizes problem-solving. prereq: [2263 or 2374 or 2573]; [2283 or 2574 or 3283] recommended
MATH 4707 - Introduction to Combinatorics and Graph Theory
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Existence, enumeration, construction, algorithms, optimization. Pigeonhole principle, bijective combinatorics, inclusion-exclusion, recursions, graph modeling, isomorphism. Degree sequences and edge counting. Connectivity, Eulerian graphs, trees, Euler's formula, network flows, matching theory. Mathematical induction as proof technique. prereq: 2243, [2283 or 3283]
MATH 4990 - Topics in Mathematics
Credits: 1.0 -4.0 [max 12.0]
Typically offered: Every Fall, Spring & Summer
MATH 5067 - Actuarial Mathematics I
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Future lifetime random variable, survival function. Insurance, life annuity, future loss random variables. Net single premium, actuarial present value, net premium, net reserves. prereq: 4065, [one sem [4xxx or 5xxx] [probability or statistics] course]
MATH 5068 - Actuarial Mathematics II
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Multiple decrement insurance, pension valuation. Expense analysis, gross premium, reserves. Problem of withdrawals. Regulatory reserving systems. Minimum cash values. Additional topics at instructor's discretion. prereq: 5067
MATH 5075 - Mathematics of Options, Futures, and Derivative Securities I
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Mathematical background (e.g., partial differential equations, Fourier series, computational methods, Black-Scholes theory, numerical methods--including Monte Carlo simulation). Interest-rate derivative securities, exotic options, risk theory. First course of two-course sequence. prereq: Two yrs calculus, basic computer skills
MATH 5076 - Mathematics of Options, Futures, and Derivative Securities II
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Mathematical background such as partial differential equations, Fourier series, computational methods, Black-Scholes theory, numerical methods (including Monte Carlo simulation), interest-rate derivative securities, exotic options, risk theory. prereq: 5075
MATH 5165 - Mathematical Logic I
Credits: 4.0 [max 4.0]
Course Equivalencies: Math 4152/5165
Typically offered: Every Fall
Theory of computability: notion of algorithm, Turing machines, primitive recursive functions, recursive functions, Kleene normal form, recursion theorem. Propositional logic. prereq: 2283 or 3283 or Phil 5201 or CSci course in theory of algorithms or instr consent
MATH 5248 - Cryptology and Number Theory
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Classical cryptosystems. One-time pads, perfect secrecy. Public key ciphers: RSA, discrete log. Euclidean algorithm, finite fields, quadratic reciprocity. Message digest, hash functions. Protocols: key exchange, secret sharing, zero-knowledge proofs. Probablistic algorithms: pseudoprimes, prime factorization. Pseudo-random numbers. Elliptic curves. prereq: 2 sems soph math
MATH 5251 - Error-Correcting Codes, Finite Fields, Algebraic Curves
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Information theory: channel models, transmission errors. Hamming weight/distance. Linear codes/fields, check bits. Error processing: linear codes, Hamming codes, binary Golay codes. Euclidean algorithm. Finite fields, Bose-Chaudhuri-Hocquenghem codes, polynomial codes, Goppa codes, codes from algebraic curves. prereq: 2 sems soph math
MATH 5335 - Geometry I
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Advanced two-dimensional Euclidean geometry from a vector viewpoint. Theorems/problems about triangles/circles, isometries, connections with Euclid's axioms. Hyperbolic geometry, how it compares with Euclidean geometry. prereq: [2243 or 2373 or 2573], [concurrent registration is required (or allowed) in 2263 or concurrent registration is required (or allowed) in 2374 or concurrent registration is required (or allowed) in 2574]
MATH 5378 - Differential Geometry
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Basic geometry of curves in plane and in space, including Frenet formula, theory of surfaces, differential forms, Riemannian geometry. prereq: [2263 or 2374 or 2573], [2243 or 2373 or 2574]; [2283 or 3283] recommended]
MATH 5385 - Introduction to Computational Algebraic Geometry
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Geometry of curves/surfaces defined by polynomial equations. Emphasizes concrete computations with polynomials using computer packages, interplay between algebra and geometry. Abstract algebra presented as needed. prereq: [2263 or 2374 or 2573], [2243 or 2373 or 2574]
MATH 5445 - Mathematical Analysis of Biological Networks
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Development/analysis of models for complex biological networks. Examples taken from signal transduction networks, metabolic networks, gene control networks, and ecological networks. prereq: Linear algebra, differential equations
MATH 5447 - Theoretical Neuroscience
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Nonlinear dynamical system models of neurons and neuronal networks. Computation by excitatory/inhibitory networks. Neural oscillations, adaptation, bursting, synchrony. Memory systems. prereq: 2243 or 2373 or 2574
MATH 5467 - Introduction to the Mathematics of Image and Data Analysis
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Background theory/experience in wavelets. Inner product spaces, operator theory, Fourier transforms applied to Gabor transforms, multi-scale analysis, discrete wavelets, self-similarity. Computing techniques. prereq: [2243 or 2373 or 2573], [2283 or 2574 or 3283 or instr consent]; [[2263 or 2374], 4567] recommended
MATH 5485 - Introduction to Numerical Methods I
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Solution of nonlinear equations in one variable. Interpolation, polynomial approximation. Methods for solving linear systems, eigenvalue problems, systems of nonlinear equations. prereq: [2243 or 2373 or 2573], familiarity with some programming language
MATH 5486 - Introduction To Numerical Methods II
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Numerical integration/differentiation. Numerical solution of initial-value problems, boundary value problems for ordinary differential equations, partial differential equations. prereq: 5485
MATH 5525 - Introduction to Ordinary Differential Equations
Credits: 4.0 [max 4.0]
Typically offered: Periodic Fall & Spring
Ordinary differential equations, solution of linear systems, qualitative/numerical methods for nonlinear systems. Linear algebra background, fundamental matrix solutions, variation of parameters, existence/uniqueness theorems, phase space. Rest points, their stability. Periodic orbits, Poincare-Bendixson theory, strange attractors. prereq: [2243 or 2373 or 2573], [2283 or 2574 or 3283]
MATH 5535 - Dynamical Systems and Chaos
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Dynamical systems theory. Emphasizes iteration of one-dimensional mappings. Fixed points, periodic points, stability, bifurcations, symbolic dynamics, chaos, fractals, Julia/Mandelbrot sets. prereq: [2243 or 2373 or 2573], [2263 or 2374 or 2574]
MATH 5583 - Complex Analysis
Credits: 4.0 [max 4.0]
Course Equivalencies: Math 3574/Math 5583
Typically offered: Every Fall, Spring & Summer
Algebra, geometry of complex numbers. Linear fractional transformations. Conformal mappings. Holomorphic functions. Theorems of Abel/Cauchy, power series. Schwarz' lemma. Complex exponential, trig functions. Entire functions, theorems of Liouville/Morera. Reflection principle. Singularities, Laurent series. Residues. prereq: 2 sems soph math [including [2263 or 2374 or 2573], [2283 or 3283]] recommended
MATH 5587 - Elementary Partial Differential Equations I
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Emphasizes partial differential equations w/physical applications, including heat, wave, Laplace's equations. Interpretations of boundary conditions. Characteristics, Fourier series, transforms, Green's functions, images, computational methods. Applications include wave propagation, diffusions, electrostatics, shocks. prereq: [2243 or 2373 or 2573], [2263 or 2374 or 2574]
MATH 5588 - Elementary Partial Differential Equations II
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Heat, wave, Laplace's equations in higher dimensions. Green's functions, Fourier series, transforms. Asymptotic methods, boundary layer theory, bifurcation theory for linear/nonlinear PDEs. Variational methods. Free boundary problems. Additional topics as time permits. prereq: [[2243 or 2373 or 2573], [2263 or 2374 or 2574], 5587] or instr consent
MATH 5651 - Basic Theory of Probability and Statistics
Credits: 4.0 [max 4.0]
Course Equivalencies: Math 5651/Stat 5101
Typically offered: Every Fall & Spring
Logical development of probability, basic issues in statistics. Probability spaces, random variables, their distributions/expected values. Law of large numbers, central limit theorem, generating functions, sampling, sufficiency, estimation. prereq: [2263 or 2374 or 2573], [2243 or 2373]; [2283 or 2574 or 3283] recommended.
MATH 5652 - Introduction to Stochastic Processes
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Random walks, Markov chains, branching processes, martingales, queuing theory, Brownian motion. prereq: 5651 or Stat 5101
MATH 5654 - Prediction and Filtering
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Markov chains, Wiener process, stationary sequences, Ornstein-Uhlenbeck process. Partially observable Markov processes (hidden Markov models), stationary processes. Equations for general filters, Kalman filter. Prediction of future values of partially observable processes. prereq: 5651 or Stat 5101
MATH 5705 - Enumerative Combinatorics
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Basic enumeration, bijections, inclusion-exclusion, recurrence relations, ordinary/exponential generating functions, partitions, Polya theory. Optional topics include trees, asymptotics, listing algorithms, rook theory, involutions, tableaux, permutation statistics. prereq: [2243 or 2373 or 2573], [2263 or 2283 or 2374 or 2574 or 3283]
MATH 5707 - Graph Theory and Non-enumerative Combinatorics
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Basic topics in graph theory: connectedness, Eulerian/Hamiltonian properties, trees, colorings, planar graphs, matchings, flows in networks. Optional topics include graph algorithms, Latin squares, block designs, Ramsey theory. prereq: [2243 or 2373 or 2573], [2263 or 2374 or 2574]; [2283 or 3283 or experience in writing proofs] highly recommended; Credit will not be granted if credit has been received for: 4707
MATH 5711 - Linear Programming and Combinatorial Optimization
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Simplex method, connections to geometry, duality theory, sensitivity analysis. Applications to cutting stock, allocation of resources, scheduling problems. Flows, matching/transportation problems, spanning trees, distance in graphs, integer programs, branch/bound, cutting planes, heuristics. Applications to traveling salesman, knapsack problems. prereq: 2 sems soph math [including 2243 or 2373 or 2573]
MATH 8301 - Manifolds and Topology
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Classification of compact surfaces, fundamental group/covering spaces. Homology group, basic cohomology. Application to degree of a map, invariance of domain/dimension. prereq: [Some point-set topology, algebra] or instr consent
MATH 8302 - Manifolds and Topology
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Smooth manifolds, tangent spaces, embedding/immersion, Sard's theorem, Frobenius theorem. Differential forms, integration. Curvature, Gauss-Bonnet theorem. Time permitting: de Rham, duality in manifolds. prereq: 8301 or instr consent
MATH 8401 - Mathematical Modeling and Methods of Applied Mathematics
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Dimension analysis, similarity solutions, linearization, stability theory, well-posedness, and characterization of type. Fourier series and integrals, wavelets, Green's functions, weak solutions and distributions. prereq: 4xxx numerical analysis and applied linear algebra or instr consent
MATH 8402 - Mathematical Modeling and Methods of Applied Mathematics
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Calculus of variations, integral equations, eigenvalue problems, spectral theory. Perturbation, asymptotic methods. Artificial boundary conditions, conformal mapping, coordinate transformations. Applications to specific modeling problems. prereq: 8401 or instr consent
MATH 8442 - Numerical Analysis and Scientific Computing
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Numerical methods for integral equations, parabolic partial differential equations, hyperbolic partial differential equations. Monte Carlo methods. prereq: 8441 or instr consent; 5477-5478 recommended for engineering and science grad students
MATH 8445 - Numerical Analysis of Differential Equations
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Finite element and finite difference methods for elliptic boundary value problems (e.g., Laplace's equation) and solution of resulting linear systems by direct and iterative methods. prereq: 4xxx numerical analysis, 4xxx partial differential equations or instr consent
MATH 8450 - Topics in Numerical Analysis
Credits: 1.0 -3.0 [max 12.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Selected topics. prereq: Grad math major or instr consent; offered as one year or one semester course as circumstances warrant
MATH 8600 - Topics in Advanced Applied Mathematics
Credits: 1.0 -3.0 [max 12.0]
Typically offered: Every Fall & Spring
Offered for one yr or one semester as circumstances warrant. Topics vary. For details, contact instructor.
MATH 8601 - Real Analysis
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Set theory/fundamentals. Axiom of choice, measures, measure spaces, Borel/Lebesgue measure, integration, fundamental convergence theorems, Riesz representation. prereq: 5616 or instr consent
MATH 8602 - Real Analysis
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Radon-Nikodym, Fubini theorems. C(X). Lp spaces (introduction to metric, Banach, Hilbert spaces). Stone-Weierstrass theorem. Basic Fourier analysis. Theory of differentiation. prereq: 8601 or instr consent
MATH 8651 - Theory of Probability Including Measure Theory
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Probability spaces. Distributions/expectations of random variables. Basic theorems of Lebesque theory. Stochastic independence, sums of independent random variables, random walks, filtrations. Probability, moment generating functions, characteristic functions. Laws of large numbers. prereq: 5616 or instr consent
MATH 8668 - Combinatorial Theory
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall
Basic enumeration, including sets and multisets, permutation statistics, inclusion-exclusion, integer/set partitions, involutions and Polya theory. Partially ordered sets, including lattices, incidence algebras, and Mobius inversion. Generating functions.
MATS 5517 - Microscopy of Materials
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
A basic introduction to electron microscopy (EM) methods and techniques for materials characterization. The course is intended for junior- and senior-level undergraduates and graduate students interested in obtaining a basic understanding of characterization with EM. Topics to be covered include an introduction to instrumentation, basics of scattering theory, and a survey of imaging, diffraction, and analytical measurement techniques. Current and emerging techniques will also be covered, including machine learning and big data for EM and time-resolved measurements. Students will research a specific topic of interest over the course of the semester, culminating in a project paper and a class presentation.
MATS 5771 - Colloids and Dispersions
Credits: 3.0 [max 3.0]
Course Equivalencies: inactive
Grading Basis: A-F or Aud
Typically offered: Every Fall
Preparation, stability, coagulation kinetics, or colloidal solutions. DLVO theory, electrokinetic phenomena. Properties of micelles, other microstructures. prereq: Physical chemistry
MATS 8001 - Structure and Symmetry of Materials
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Comprehensive description of structure of materials, including metals, semiconductors, organic crystals, polymers, and liquid crystals. Atomic and molecular ordering, influence of intermolecular forces on symmetry and structure. Principles of scattering and use of X-ray, neutron, and electron diffraction. prereq: MatS and ChEn majors must take this course for a grade
MATS 8003 - Electronic Properties
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Basic physical theory of bonding in metals, alloys, and semiconductors. Review of modern physics, statistical physics, and solid state physics. Structure of matter emphasizing electronic processes. Techniques for predicting and understanding electronic structure of solids. Transport theory, elementary theory of magnetism, and superconductivity. prereq: instr consent
MATS 8995 - Special Topics
Credits: 1.0 -4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
New or experimental courses offered by department or visiting faculty.
ME 5113 - Aerosol/Particle Engineering
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Kinetic theory, definition, theory and measurement of particle properties, elementary particle mechanics, particle statistics; Brownian motion and diffusion, coagulation, evaporation and condensation, sampling and transport. prereq: CSE upper div or grad student
ME 5223 - Materials in Design
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Fundamental properties of engineering materials. Fabrication, treatment. Physical/corrosive properties. Failure mechanism, cost/value analysis as related to material selection/specification. prereq: 3221, ME upper division or grad student
ME 5228 - Introduction to Finite Element Modeling, Analysis, and Design
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Finite elements as principal analysis tool in computer-aided design (CAD); theoretical issues and implementation aspects for modeling and analyzing engineering problems encompassing stress analysis, heat transfer, and flow problems for linear situations. One-, two-, and three-dimensional practical engineering applications. prereq: CSE upper div or grad, 3221, AEM 3031, CSci 1113, MatS 2001
ME 5241 - Computer-Aided Engineering
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Apply computer-aided engineering to mechanical design. Engineering design projects and case studies using computer-aided design and finite element analysis software; design optimization and computer graphical presentation of results. prereq: 3222, CSci 1113 or equiv, CSE upper div or grad
ME 5243 - Advanced Mechanism Design
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Summer
Analytical methods of kinematic, dynamic, and kinetoelastodynamic analysis and synthesis of mechanisms. Computerized design for function, path, and motion generation based on Burmeister theory. prereq: CSE upper div or grad, 3222 or equiv, basic kinematics and dynamics of machines; knowledge of CAD packages such as Pro-E recommended
ME 5247 - Applied Stress Analysis
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Spring Odd Year
Intermediate-level solid mechanics with application to common machine elements such as unsymmetrical beams, non-circular shafts and plates. Stress functions. Introduction to energy methods for stress analysis. Experimental methods for measuring strains and determining related stresses, with lab. prereq: AEM 3031, MatS 2001, ME 3221
ME 5281 - Feedback Control Systems
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Continuous and discrete time feedback control systems. Frequency response, stability, poles and zeros; transient responses; Nyquist and Bode diagrams; root locus; lead-lag and PID compensators, Nichols-Ziegler design method. State-space modeling/control. Digital implementation. Computer-aided design and analysis of control systems. prereq: 3281
ME 5286 - Robotics
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
The course deals with two major components: robot manipulators (more commonly known as the robot arm) and image processing. Lecture topics covered under robot manipulators include their forward and inverse kinematics, the mathematics of homogeneous transformations and coordinate frames, the Jacobian and velocity control, task programming, computational issues related to robot control, determining path trajectories, reaction forces, manipulator dynamics and control. Topics under computer vision include: image sensors, digitization, preprocessing, thresholding, edge detection, segmentation, feature extraction, and classification techniques. A weekly 2 hr. laboratory lasting for 8-9 weeks, will provide students with practical experience using and programming robots; students will work in pairs and perform a series of experiments using a collaborative robot. prereq: [3281 or equiv], [upper div ME or AEM or CSci or grad student]
ME 5312 - Solar Thermal Technologies
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Spring Odd Year
Solar radiation fundamentals. Measurement/processing needed to predict solar irradiance dependence on time, location, and orientation. Characteristics of components in solar thermal systems: collectors, heat exchangers, thermal storage. System performance, low-temperature applications. Concentrating solar energy, including solar thermo-chemical processes, to produce hydrogen/solar power systems and photovoltaics. Solar design project. prereq: [3333, CSE upper Div] or grad student
ME 5344 - Thermodynamics of Fluid Flow With Applications
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Fall Odd Year
Conservation of mass, momentum, energy. Relevant thermodynamic properties. Nozzles, diffusers, thrust producers, shocks. Fluid-wall frictional interactions. Wall heat transfer, internal heat release. Temperature recovery. Mass addition. prereq: ME 3331, ME 3332, completed, or concurrent registration in ME 3333; admitted to upper division/ME major or grad student
ME 5351 - Computational Heat Transfer
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Numerical solution of heat conduction/analogous physical processes. Develop/use computer program to solve complex problems involving steady/unsteady heat conduction, flow/heat transfer in ducts, flow in porous media. prereq: 3333, CSE upper div or grad student
ME 5461 - Internal Combustion Engines
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Basic spark ignition and diesel engine principles, air, fuel-air and actual engine cycles, cycle modeling, combustion and emissions, knock phenomena, air flow and volumetric efficiency, mixture requirements, ignition requirements and performance. Lectures/complementary labs. prereq: CSE upper div or grad student, C or better in [3332, 3333] or 3324
ME 8228 - Finite Elements in Multidisciplinary Flow/Thermal/Stress and Manufacturing Applications
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall & Spring
Multidisciplinary and coupled effects involving flow/heat transfer/stress. In-depth understanding of modeling and analysis in each discipline. Coupling multi-disciplines for engineering problems. Applications to manufacturing and process modeling of, e.g., metals, alloys, polymers. prereq: 3222, 5341, AEM 3031, CSci 1113
ME 8229 - Finite Element Methods for Computational Mechanics: Transient/Dynamic Problems
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Computational mechanics involving transient or dynamic situations; development and analysis of computational algorithms. Stability and accuracy of algorithms, convergence issues; linear/nonlinear situations. Implicit, explicit, mixed, and variable time discretization approaches; modal-based methods for engineering problems prereq: 5228 or equiv, 5341, AEM 3031, CSci 1113
ME 8243 - Topics in Design: Advanced Materials
Credits: 4.0 [max 12.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall & Spring
Topics vary with each offering.
ME 8253 - Computational Nanomechanics
Credits: 3.0 [max 3.0]
Course Equivalencies: ME 8253/SCIC 8253
Prerequisites: CSE grad student
Typically offered: Every Spring
Fundamentals of mechanical properties in nanometer scale. Role of discrete structure and underlying atomic, molecular, and interfacial forces are illustrated with modern examples. Overview of computational atomistic methods. Lectures, hands-on computing using publicly available or personally developed scientific software packages. prereq: CSE grad student
ME 8254 - Fundamentals of Microelectromechanical Systems (MEMS)
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Spring
Major classes, components, and applications of MEMS. Principles behind operation of MEMS devices/ systems. Standard microfabrication techniques. Unique requirements, environments, and applications of MEMS. Students apply microfabrication techniques/applications to design/manufacture of a MEMS device or microsystem.
ME 8281 - Advanced Control System Design-1
Credits: 3.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Loop Shaping. Review of controllability/observability. LQR/LQG/LTR. Repetitive control. Input shaping. Tracking control (feedforward, precompensation). Lyapunov stability. System identification. prereq: 5281
ME 8343 - Radiation
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Advanced radiation heat transfer problems. Physics foundation for radiation. Materials properties. Radiation transfer problems. Solution methods for integro-differential equations. Statistical methods. Multi-mode heat transfer. prereq: Undergrad class in heat transfer or instr consent
MPHY 5170 - Radiation Therapy Physics I
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Theoretical/experimental aspects of radiological physics. Physical properties of various ionizing radiations, interactions of ionizing radiations with matter, methods of radiation dose measurement. prereq: instr consent
MPHY 5171 - Medical and Health Physics of Imaging I
Credits: 3.0 [max 3.0]
Course Equivalencies: BPhy 5171/TRad 7171
Typically offered: Every Fall
Physics of diagnostic imaging: specification/quantification of image quality, X-ray production, image receptors, magnetic resonance imaging, radiation exposure and protection. Special imaging techniques, including mammography, computed tomography, and direct digital image capture. prereq: 5170 or instr consent
MPHY 5174 - Medical and Health Physics of Imaging II
Credits: 3.0 [max 3.0]
Course Equivalencies: BPhy 5174/TRad 7174
Typically offered: Every Spring
Physics of diagnostic imaging. Ultrasound, theoretical/experimental applications of radionuclides in medicine and biology. Counting statistics and imaging systems associated with radiopharmaceuticals, radiation dosimetry, and safety in nuclear medicine. prereq: 5170 or instr consent
MPHY 8147 - Advanced Physics of Magnetic Resonance Imaging (MRI)
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
NMR (nuclear magnetic resonance) and MRI physics, spatial selection and encoding, imaging hardware and system engineering. Imaging sequences, associated contrast/resolution. Recent developments in MRI. prereq: 5174 or instr consent
NPSE 8101 - Nanoparticle Science and Engineering Seminar
Credits: 1.0 [max 1.0]
Grading Basis: S-N or Aud
Typically offered: Every Fall & Spring
Broad overview of current research in nanoparticle science and engineering. Topics include areas of nanoparticle synthesis, nanoparticles characterization, nanoparticle-based materials and devices, environmental impact of nanoparticles, and instrumentation for nanoparticle research. Speakers from the University of Minnesota as well as external experts. prereq: CSE grad student or
NSC 5040 - Brain Networks: From Connectivity to Dynamics
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Fall Odd Year
Brain networks. Application of emerging science of complex networks to studies of the brain. Network approaches that provide fundamental insights into the integrative nature of brain function and its relation to the brain structure. Organization of brain networks and dynamics at multiple spatial scales, ranging from the microscale of single neurons and synapses, to mesoscale of anatomical cell groupings and their projections, and to the macroscale of brain regions and pathways. Experimental studies, including electrophysiology, voltage-sensitive dye imaging, electroencephalography, magnetoencephalography, and functional magnetic resonance imaging, that allow mapping network elements and structural/functional connectivity between them at different temporal and spatial scales will be considered. Experimental/theoretical perspectives.
NSC 5202 - Theoretical Neuroscience: Systems and Information Processing
Credits: 3.0 [max 3.0]
Course Equivalencies: NSc 5202/Phsl 5202
Typically offered: Every Spring
Concepts of computational/theoretical neuroscience. Distributed representations and information theory. Methods for single-cell modeling, including compartmental/integrate-and-fire models. Learning rules, including supervised, unsupervised, and reinforcement learning models. Specific systems models from current theoretical neuroscience literature. Lecture/discussion. Readings from current scientific literature. prereq: [3101, 3102W] recommended
NSC 5203 - Basic and Clinical Vision Science
Credits: 3.0 [max 3.0]
Typically offered: Spring Even Year
Basic and clinical vision science. prereq: instr consent
NSC 5561 - Systems Neuroscience
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Principles of organization of neural systems forming the basis for sensation/movement. Sensory-motor/neural-endocrine integration. Relationships between structure and function in nervous system. Team taught. Lecture, laboratory. prereq: NSc grad student or instr consent
PHSL 5061 - Principles of Physiology for Biomedical Engineering
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Human physiology with emphasis on quantitative aspects. Organ systems (circulation, respiration, renal, gastrointestinal, endocrine, muscle, central and peripheral nervous systems), cellular transport processes, and scaling in biology. prereq: Biomedical engineering grad, one yr college chem and physics and math through integral calculus
PHSL 5101 - Human Physiology
Credits: 5.0 [max 5.0]
Course Equivalencies: INMD 6814/PHSL 5101
Typically offered: Every Spring
Survey of human physiology: Cardiovascular, muscle, respiratory, gastrointestinal, nutrition, renal physiology. Integrative, systems approach. Emphasizes normal function. prereq: Grad student
PHSL 5201 - Computational Neuroscience I: Membranes and Channels
Credits: 3.0 [max 3.0]
Course Equivalencies: NSc 5201/Phsl 5201
Typically offered: Every Fall
Neural excitation (ion channels, excitation models, effects of neural morphology) using UNIX workstations to simulate empirical results. Includes the Hodgkin-Huxley model, nonlinear dynamic systems analysis, voltage and ligand gated ion channels, ion transport theories, and impulse initiation and propagation. prereq: calculus through differential equations
PHYS 4001 - Analytical Mechanics
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Analytic Newtonian mechanics. Mathematics beyond prerequisites developed as required. Prereq: PHYS 2503/2503H or equivalent, PHYS 3041
PHYS 4002 - Electricity and Magnetism
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Classical theory of electromagnetic fields using vector algebra and vector calculus. prereq: PHYS 3041, PHYS 2503/2503H or equivalent
PHYS 4041 - Computational Methods in the Physical Sciences
Credits: 4.0 [max 4.0]
Course Equivalencies: Ast 4041/Phys 4041
Typically offered: Periodic Fall & Spring
Introduction to using computer programs to solve problems in physical sciences. Selected numerical methods, mapping problems onto computational algorithms. Arranged lab. Prereq: PHYS 3041
PHYS 4051 - Methods of Experimental Physics I
Credits: 5.0 [max 5.0]
Typically offered: Every Fall
Contemporary experimental techniques. Introduction to modern analog and digital electronics from an experimental viewpoint. Use of computers for data acquisition and experimental control. Statistics of data analysis. Prereq or Concurrent PHYS 3605W, PHYS 3041
PHYS 4052W - Methods of Experimental Physics II (WI)
Credits: 5.0 [max 5.0]
Typically offered: Every Spring
Second semester of laboratory sequence. Contemporary experimental techniques illustrated by experiments with data analysis. Students design and execute an experimental project. Lectures on specialized topics of professional concern. prereq: PHYS 4051
PHYS 4101 - Quantum Mechanics
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Mathematical techniques of quantum mechanics. Schrodinger Equation and simple applications. General structure of wave mechanics. Operator methods, perturbation theory, radiation from atoms. Prereq: PHYS 3041, PHYS 2601
PHYS 4121W - History of 20th-Century Physics (WI)
Credits: 3.0 [max 3.0]
Course Equivalencies: HSci 4121/Phys 4121
Grading Basis: OPT No Aud
Typically offered: Periodic Spring
The transition from classical to modern physics (relativity, quantum) and its architects (from Planck and Einstein to Heisenberg and Schrödinger). The WWII bomb projects in the US and in Germany. Post-war developments (solid state, particle physics). Prereq: calculus or permission from the instructor.
PHYS 4201 - Statistical and Thermal Physics
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Principles of thermodynamics and statistical mechanics. Selected applications such as kinetic theory, transport theory, and phase transitions. Prereq: PHYS 3041, PHYS 2201, PHYS 2601
PHYS 4211 - Introduction to Solid-State Physics
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
A modern presentation of the properties of solids. Topics include vibrational and electronic properties of solids; diffraction of waves in solids and electron band structure. Other possible topics include optical properties, magnetic phenomena, and superconductivity. prereq: 2201, 4101
PHYS 4303 - Electrodynamics and Waves
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Analytical mechanics. Electricity/magnetism, including mechanical/electromagnetic wave phenomena. Physical/geometrical optics. Prereq: PHYS 4002
PHYS 4511 - Introduction to Nuclear and Particle Physics
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Fundamental particles and Standard Model. Symmetries/quarks, models of nuclei, interactions between particles/nuclei, tests of conservation laws, fission/fusion. prereq: 4101
PHYS 4611 - Introduction to Space Physics
Credits: 3.0 [max 3.0]
Typically offered: Fall Odd Year
Dynamics of charged particles/plasmas in space. Physics of the Sun and solar wind. Solar/galactic cosmic rays. Interactions of solar wind with planetary magnetospheres. Dynamics of Magnetosphere. Formation of the aurora. Physics of radiation belts. prereq: PHYS 4001, PHYS 4002
PHYS 4621 - Introduction to Plasma Physics
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Basic properties of collisionless, magnetized plasmas, single particle motion, plasmas as fluids, magnetohydrodynamics, waves in plasmas, equilibrium, instabilities, kinetic theory/shocks. Prereq: PHYS 4001, PHYS 4002
PHYS 4911 - Introduction to Biopolymer Physics
Credits: 3.0 [max 3.0]
Course Equivalencies: Phys 4911/5081
Typically offered: Every Spring
Introduction to biological and soft condensed matter physics. Emphasizes physical ideas necessary to understand behavior of macromolecules and other biological materials. Elements of thermodynamics and statistical mechanics are presented as needed. Prereq: PHYS 2201 or equivalent
PHYS 5001 - Quantum Mechanics I
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Schrodinger equation: bound state and scattering problems in one dimension. Spherically symmetric problems in three dimensions, angular momentum, and the hydrogen atom. Approximation methods for stationary states. Time-dependent perturbation theory. Operators and state vectors: general formalism of quantum theory. prereq: 4101 or equiv or instr consent
PHYS 5002 - Quantum Mechanics II
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Symmetry in quantum mechanics, space-time symmetries and the rotation group, Clebsch-Gordan coefficients and the Wigner-Eckart theorem. Scattering theory. Method of second quantization with elementary applications. Relativistic wave equations including Dirac equation. prereq: 5001 or equiv
PHYS 5011 - Classical Physics I
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Classical mechanics: Lagrangian/Hamiltonian mechanics, orbital dynamics, rigid body motion, special relativity. prereq: 4001, 4002 or instr consent
PHYS 5012 - Classical Physics II
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Classical electromagnetism: electrostatics, magnetostatics, Maxwell's equations, electromagnetic waves, radiation, interaction of charged particles with matter. prereq: 5011 or instr consent
PHYS 5041 - Mathematical Methods for Physics
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Survey of mathematical techniques needed in analysis of physical problems. Emphasizes analytical methods. prereq: 2601 or grad student
PHYS 5081 - Introduction to Biopolymer Physics
Credits: 3.0 [max 3.0]
Course Equivalencies: Phys 4911/5081
Typically offered: Every Spring
Introduction to biological and soft condensed matter physics. Emphasizes physical ideas necessary to understand behavior of macromolecules and other biological materials. prereq: PHYS 2201 or equivalent
PHYS 5201 - Thermal and Statistical Physics
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Equilibrium Statistical Mechanics. General Principles of Statistical Mechanics: Ensembles. Derivation of Thermodynamics from statistical principles. Classical Systems. Quantum Statistical Mechanics: Fundamentals. Photons. Ideal Fermi & Bose Gases. Non-ideal gases. Introduction to Phase Transitions. prereq: [[4101, 4201] or equiv] previous exposure to thermodynamics, introductory statistical physics
PHYS 5701 - Solid-State Physics for Engineers and Scientists
Credits: 4.0 [max 4.0]
Typically offered: Periodic Fall & Spring
Crystal structure and binding; diffraction; phonons; thermal and dielectric properties of insulators; free electron model; band structure; semiconductors. prereq: Grad or advanced undergrad in physics or engineering or the sciences
PHYS 8001 - Advanced Quantum Mechanics
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Topics in non-relativistic quantum mechanics; second quantization. Introduction to Diagrammatic and Green's function techniques and to relativistic wave equations. Application of relativistic perturbation theory to particle interactions with electromagnetic field. Invariant interactions of elementary particles. prereq: 5002 or instr consent
PHYS 8711 - Solid-State Physics I
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Fundamental properties of solids. Electronic structure and transport in metals and semiconductors. Properties of disordered materials. prereq: 4211, 5002 or instr consent
PHYS 8712 - Solid-State Physics II
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Fundamental properties of solids. Electronic structure and transport in metals and semiconductors. Properties of disordered materials. prereq: 8711 or instr consent
PMB 4121 - Microbial Ecology and Applied Microbiology
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Evolution/structure of microbial communities. Population interaction within ecosystems. Quantitative/habitat ecology. Biogeochemical cycling. Molecular microbial ecology, gene transfer in the environment. Molecular phylogeny of microorganisms. Application of microbes in agriculture. Production of commodity chemicals, drugs, and other high-value products. prereq: 3301
PSY 5036W - Computational Vision (WI)
Credits: 3.0 [max 3.0]
Typically offered: Fall Even Year
Applications of psychology, neuroscience, computer science to design principles underlying visual perception, visual cognition, action. Compares biological/physical processing of images with respect to image formation, perceptual organization, object perception, recognition, navigation, motor control. prereq: [[3031 or 3051], [Math 1272 or equiv]] or instr consent
PSY 5038W - Introduction to Neural Networks (WI)
Credits: 3.0 [max 3.0]
Typically offered: Fall Odd Year
Parallel distributed processing models in neural/cognitive science. Linear models, Hebbian rules, self-organization, non-linear networks, optimization, representation of information. Applications to sensory processing, perception, learning, memory. prereq: [[3061 or NSC 3102], [MATH 1282 or 2243]] or instr consent
SSM 5612 - Systems Approach to Building Science and Construction
Credits: 4.0 [max 4.0]
Course Equivalencies: SSM 3612/SSM 5612
Typically offered: Every Fall
Dynamic/interrelated issues of energy, moisture control, indoor air quality in residential bldgs. Emphasizes design, construction, and operational aspects to provide an energy efficient, durable structure, and healthy living environment. Interaction between moisture and wood products within building system. prereq: Graduate Student
SSM 5614 - Building Systems Performance: Testing & Diagnostics
Credits: 2.0 [max 2.0]
Course Equivalencies: SSM 4614/SSM 5614
Typically offered: Spring Even Year
Theoretical basis for performance testing. Diagnostics applications for residential structures. Focuses on existing structures and retrofit/remedial applications. Digital differential pressure gauges, blower doors, airflow hoods/grids, duct pressure testing, infrared thermography. Hands-on sessions for equipment use, problem solving. prereq: Grad student or instr consent
STAT 4101 - Theory of Statistics I
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Random variables/distributions. Generating functions. Standard distribution families. Data summaries. Sampling distributions. Likelihood/sufficiency. prereq: Math 1272 or Math 1372 or Math 1572H
STAT 4102 - Theory of Statistics II
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Estimation. Significance tests. Distribution free methods. Power. Application to regression and to analysis of variance/count data. prereq: STAT 4101
STAT 5021 - Statistical Analysis
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Intensive introduction to statistical methods for graduate students needing statistics as a research technique. prereq: college algebra or instr consent; credit will not be granted if credit has been received for STAT 3011
STAT 5101 - Theory of Statistics I
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Logical development of probability, basic issues in statistics. Probability spaces. Random variables, their distributions and expected values. Law of large numbers, central limit theorem, generating functions, multivariate normal distribution. prereq: (MATH 2263 or MATH 2374 or MATH 2573H), (MATH 2142 or CSCI 2033 or MATH 2373 or MATH 2243)
STAT 5102 - Theory of Statistics II
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Sampling, sufficiency, estimation, test of hypotheses, size/power. Categorical data. Contingency tables. Linear models. Decision theory. prereq: [5101 or Math 5651 or instr consent]
STAT 5201 - Sampling Methodology in Finite Populations
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Simple random, systematic, stratified, unequal probability sampling. Ratio, model based estimation. Single stage, multistage, adaptive cluster sampling. Spatial sampling. prereq: 3022 or 3032 or 3301 or 4102 or 5021 or 5102 or instr consent
STAT 5302 - Applied Regression Analysis
Credits: 4.0 [max 4.0]
Typically offered: Every Fall, Spring & Summer
Simple, multiple, and polynomial regression. Estimation, testing, prediction. Use of graphics in regression. Stepwise and other numerical methods. Weighted least squares, nonlinear models, response surfaces. Experimental research/applications. prereq: 3032 or 3022 or 4102 or 5021 or 5102 or instr consent Please note this course generally does not count in the Statistical Practice BA or Statistical Science BS degrees. Please consult with a department advisor with questions.
STAT 5303 - Designing Experiments
Credits: 4.0 [max 4.0]
Typically offered: Every Fall, Spring & Summer
Analysis of variance. Multiple comparisons. Variance-stabilizing transformations. Contrasts. Construction/analysis of complete/incomplete block designs. Fractional factorial designs. Confounding split plots. Response surface design. prereq: 3022 or 3032 or 3301 or 4102 or 5021 or 5102 or instr consent
STAT 5401 - Applied Multivariate Methods
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall
Bivariate and multivariate distributions. Multivariate normal distributions. Analysis of multivariate linear models. Repeated measures, growth curve, and profile analysis. Canonical correlation analysis. Principal components and factor analysis. Discrimination, classification, and clustering. pre-req: STAT 3032 or 3301 or 3022 or 4102 or 5021 or 5102 or instr consent Although not a formal prerequisite of this course, students are encouraged to have familiarity with linear algebra prior to enrolling. Please consult with a department advisor with questions.
STAT 5421 - Analysis of Categorical Data
Credits: 3.0 [max 3.0]
Typically offered: Every Fall & Spring
Varieties of categorical data, cross-classifications, contingency tables. Tests for independence. Combining 2x2 tables. Multidimensional tables/loglinear models. Maximum-likelihood estimation. Tests for goodness of fit. Logistic regression. Generalized linear/multinomial-response models. prereq: STAT 3022 or 3032 or 3301 or 5302 or 4051 or 8051 or 5102 or 4102
STAT 5511 - Time Series Analysis
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Characteristics of time series. Stationarity. Second-order descriptions, time-domain representation, ARIMA/GARCH models. Frequency domain representation. Univariate/multivariate time series analysis. Periodograms, non parametric spectral estimation. State-space models. prereq: STAT 4102 or STAT 5102
STAT 8053 - Applied Statistical Methods 3: Multivariate Analysis and Advanced Regression
Credits: 3.0 [max 3.0]
Prerequisites: PhD student in stat or DGS permission and 8052
Grading Basis: A-F or Aud
Typically offered: Every Fall
Standard multivariate analysis. Multivariate linear model, classification, clustering, principal components, factor analysis, canonical correlation. Topics in advanced regression. prereq: PhD student in stat or DGS permission and 8052
STAT 8054 - Statistical Methods 4: Advanced Statistical Computing
Credits: 3.0 [max 3.0]
Prerequisites: STAT 8053 or #
Grading Basis: A-F or Aud
Typically offered: Every Spring
Optimization, numerical integration, Markov chain Monte Carlo, related topics. prereq: STAT 8053 or instr consent
STAT 8101 - Theory of Statistics 1
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Review of linear algebra. Introduction to probability theory. Random variables, their transformations/expectations. Standard distributions, including multivariate Normal distribution. Probability inequalities. Convergence concepts, including laws of large numbers, Central Limit Theorem. delta method. Sampling distributions. prereq: Statistics grad major or instr consent
STAT 8111 - Mathematical Statistics I
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Probability theory, basic inequalities, characteristic functions, and exchangeability. Multivariate normal distribution. Exponential family. Decision theory, admissibility, and Bayes rules. prereq: [5102 or 8102 or instr consent], [[Math 5615, Math 5616] or real analysis], matrix algebra
STAT 8501 - Introduction to Stochastic Processes with Applications
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall
Markov chains in discrete and continuous time, renewal processes, Poisson process, Brownian motion, and other stochastic models encountered in applications. prereq: 5101 or 8101
STAT 8931 - Advanced Topics in Statistics
Credits: 3.0 [max 12.0]
Typically offered: Periodic Fall & Spring
Topics vary according to student needs/available staff.
STAT 8932 - Advanced Topics in Statistics
Credits: 3.0 [max 12.0]
Typically offered: Periodic Fall & Spring
Topics vary according to student needs/available staff.
EE 4111 - Advanced Analog Electronics Design
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Basic integrated circuit building blocks of differential amplifiers, high bandwidth, instrumentation amplifiers. Current/voltage references. Feedback, stability, and noise in electronic circuits. Integral lab. prereq: 3015, 3115
EE 4161W - Energy Conversion and Storage (WI)
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Fundamental physics/chemistry of selected energy conversion and energy storage devices. Connections with their electric power applications. Role of grid, application to electric vehicles. Lectures, lab, student presentations. prereq: 3161 or instr consent
EE 4163 - Energy Conversion and Storage Laboratory
Credits: 1.0 [max 1.0]
Typically offered: Every Spring
Provides laboratory experiences with the topics of 4161W, including the fundamental physics and chemistry of selected energy conversion and energy storage devices, their application, and their connection strategies in electric power applications. prereq: concurrent registration is required (or allowed) in 4161W
EE 4231 - Linear Control Systems: Designed by Input/Output Methods
Credits: 3.0 [max 3.0]
Course Equivalencies: AEM 4321/EE 4231
Typically offered: Every Fall
Modeling, characteristics, performance of feedback control systems. Stability, root locus, frequency response methods. Digital implementation, hardware considerations. prereq: [3015, [upper div CSE or grad student in CSE major]] or instr consent
EE 4233 - State Space Control System Design
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
State space models, performance evaluation, numerical issues for feedback control. Stability, state estimation, quadratic performance. Implementation, computational issues. prereq: [3015, upper div CSE] or instr consent
EE 4235 - Linear Control Systems Laboratory
Credits: 1.0 [max 1.0]
Typically offered: Every Fall
Lab to accompany 4231. prereq: 4231 or concurrent registration is required (or allowed) in 4231
EE 4237 - State Space Control Laboratory
Credits: 1.0 [max 1.0]
Typically offered: Every Spring
Lab to accompany 4233. prereq: 4233 or concurrent registration is required (or allowed) in 4233; no cr for [EE or CompE] grad students
EE 4301 - Digital Design With Programmable Logic
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Summer
Introduction to system design/simulation. Design using Verilog code/synthesis. Emulation using Verilog code. prereq: 2301, [1301 or CSCI 1113 or CSCI 1901]
EE 4303 - Introduction to Programmable Devices Laboratory
Credits: 1.0 [max 1.0]
Course Equivalencies: EE 4301/EE 4303
Typically offered: Periodic Spring
Verilog Language. Combinatorial and sequential logic synthesis with Verilog. Implementation in Field Programmable Gate Arrays (FPGAs). prereq: 2301, 2361; cannot receive cr for 4303 if cr granted for EE 4301
EE 4341 - Embedded System Design
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Microcontroller interfacing for embedded system design. Exception handling/interrupts. Memory Interfacing. Parallel/serial input/output methods. System Buses and protocols. Serial Buses and component interfaces. Microcontroller Networks. Real-Time Operating Systems. Integral lab. prereq: 2301, 2361, upper div CSE
EE 4363 - Computer Architecture and Machine Organization
Credits: 4.0 [max 4.0]
Course Equivalencies: CSci 4203/EE 4363
Typically offered: Every Fall & Spring
Introduction to computer architecture. Aspects of computer systems, such as pipelining, memory hierarchy, and input/output systems. Performance metrics. Examines each component of a complicated computer system. prereq: 2361
EE 4389W - Introduction to Predictive Learning (WI)
Credits: 3.0 [max 3.0]
Typically offered: Fall Odd Year
Empirical inference and statistical learning. Classical statistical framework, model complexity control, Vapnik-Chervonenkis (VC) theoretical framework, philosophical perspective. Nonlinear methods. New types of inference. Application studies. prereq: [3025, ECE student] or STAT 3022; computer programming or MATLAB or similar environment is recommended for ECE students
EE 4501 - Communications Systems
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Systems for transmission/reception of digital/analog information. Characteristics/design of wired/wireless communication systems. Baseband, digital, and carrier-based techniques. Modulation. Coding. Electronic noise and its effects on design/performance. prereq: 3025
EE 4505 - Communications Systems Laboratory
Credits: 1.0 [max 1.0]
Typically offered: Every Fall
Experiments in analysis/design of wired/wireless communication systems. Lab to accompany 4501. prereq: 4501 or concurrent registration is required (or allowed) in 4501
EE 4541 - Digital Signal Processing
Credits: 3.0 [max 3.0]
Typically offered: Every Fall & Summer
Review of linear discrete time systems and sampled/digital signals. Fourier analysis, discrete/fast Fourier transforms. Interpolation/decimation. Design of analog, infinite-impulse response, and finite impulse response filters. Quantization effects. prereq: [3015, 3025] or instr consent
EE 4607 - Wireless Hardware System Design
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Random processes, noise, modulation, error probabilities. Antenna opertaion, power transfer between antennas, rf propagation phenomena, transmitters/receivers, transmission lines, effect of antenna performance on system performance, rf/microwave device technologies, small-signal amplifiers, mixers, power amplifiers, rf oscillators. prereq: [3015, 3115, 3601, CSE student] or dept consent
EE 4616 - Antennas: Theory, Analysis, and Design
Credits: 3.0 [max 3.0]
Course Equivalencies: EE 4616/EE 5616
Typically offered: Every Fall
With the widespread use of cell phones autonomous vehicles, and the coming of the Internet of Things, there is an increasing need to understand wireless communications and radar sensors. A key component of these systems is the antenna. The purpose of this course is to help the student develop knowledge in the area of antennas. This involves understanding the parameters that are used to characterize antennas and how these effect system performance. An important aspect of the course is to provide the student with an understanding of the operating principles behind the most commonly used antennas. This is followed with exposure to basic design principles. These can be used to perform antenna design or can be used as starting points for design using an electromagnetic simulator. As part of the course, students will be exposed to simulator use through homework assignments and course project work. [EE 3601 or equivalent]
EE 4701 - Electric Drives
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
AC/DC electric-machine drives for speed/position control. Integrated discussion of electric machines, power electronics, and control systems. Computer simulations. Applications in electric transportation, robotics, process control, and energy conservation. prereq: 3015
EE 4703 - Electric Drives Laboratory
Credits: 1.0 [max 1.0]
Typically offered: Every Spring
Laboratory to accompany 4701. Simulink-based simulations of electric machines/drives in applications such as energy conservation and motion control in robotics. prereq: 4701 or concurrent registration is required (or allowed) in 4701
EE 4721 - Introduction to Power System Analysis
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
AC power systems. Large power system networks. Mathematics/techniques of power flow analysis. Short-circuit analysis, transient stability analysis. Use of power system simulation program for design. prereq: 2011
EE 4722 - Power System Analysis Laboratory
Credits: 1.0 [max 1.0]
Typically offered: Every Fall
Lab analysis of AC power systems, power system networks, power flow, short circuit, transient stability. prereq: 4721 or concurrent registration is required (or allowed) in 4721
EE 4741 - Power Electronics
Credits: 3.0 [max 4.0]
Typically offered: Every Fall
Switch-mode power electronics. Switch-mode DC power supplies. Switch-mode converters for DC and AC motor drives, wind/photovoltaic inverters, interfacing power electronics equipment with utility system. Power semiconductor devices, magnetic design, electro-magnetic interference (EMI). prereq: 3015, 3115
EE 4743 - Switch-Mode Power Electronics Laboratory
Credits: 1.0 [max 1.0]
Typically offered: Every Fall
Laboratory to accompany 4741. PSpice-/Simulink-based simulations of converters, topologies, and control in switch-mode dc power supplies, motor drives for motion control, and inverters for interfacing renewable energy sources to utility grid. prereq: 4741 or concurrent registration is required (or allowed) in 4741
EE 5041 - Industrial Assignment for Graduate Students
Credits: 1.0 [max 1.0]
Grading Basis: S-N only
Typically offered: Every Fall, Spring & Summer
Optional industrial work assignment. Evaluation based on student's formal written report covering semester's work assignment. This course counts for 6 credits of Academic Progress for the semester in which it is taken. prereq: Consent of Advisor and Office of the DGS
EE 8190 - Electronics Seminar
Credits: 1.0 [max 3.0]
Grading Basis: S-N or Aud
Typically offered: Every Fall & Spring
Current literature, individual assignments. prereq: instr consent
EE 8210 - System Theory Seminar
Credits: 1.0 [max 3.0]
Grading Basis: S-N or Aud
Typically offered: Periodic Fall & Spring
Current literature, individual assignments.
EE 8230 - Control Theory Seminar
Credits: 1.0 [max 3.0]
Grading Basis: S-N or Aud
Typically offered: Periodic Fall & Spring
Current literature, individual assignments.
EE 8360 - Computer Systems Seminar
Credits: 1.0 [max 3.0]
Grading Basis: S-N or Aud
Typically offered: Every Fall & Spring
Current literature, individual assignments.
EE 8370 - Computer Aided Design Seminar
Credits: 1.0 [max 3.0]
Grading Basis: S-N or Aud
Typically offered: Every Fall & Spring
Current literature, individual assignments. prereq: [EE or CompE or CSci] grad major, instr consent
EE 8500 - Seminar: Communications
Credits: 1.0 [max 3.0]
Grading Basis: S-N or Aud
Typically offered: Every Fall & Spring
Current literature, individual assignments.
EE 8610 - Seminar: Electronics, Fields, and Photonics
Credits: 1.0 [max 3.0]
Grading Basis: S-N or Aud
Typically offered: Every Fall & Spring
Students are assigned readings from current literature and make individual presentations to class. From time to time outside speakers present research papers. prereq: EE grad major or instr consent
EE 8660 - Seminar: Magnetics
Credits: 1.0 [max 3.0]
Grading Basis: S-N or Aud
Typically offered: Every Fall & Spring
Current literature, individual assignments.
EE 8920 - Teaching Experience in Electrical and Computer Engineering
Credits: 1.0 [max 3.0]
Grading Basis: S-N only
Typically offered: Every Spring
Coteach class under guidance of faculty mentor. Students directly teach approximately half of the classes. Feedback to improve teaching effectiveness. Meet regularly with peers and instructor to discuss teaching concerns/issues. prereq: PhD candidate in electrical engineering, passed written preliminary exam
EE 8925 - Ethics in Electrical and Computer Engineering
Credits: 1.0 [max 1.0]
Grading Basis: S-N or Aud
Typically offered: Every Fall
Topics on issues such as data integrity, professional conduct, authorship, plagiarism, patents, copyrights, conflicts, and disclosures. Students study cases, present findings, and write report. prereq: Grad student in electrical engineering
EE 8940 - Special Investigations
Credits: 1.0 -3.0 [max 3.0]
Typically offered: Every Fall, Spring & Summer
Studies of approved theoretical or experimental topics. prereq: 1-3 cr [may be repeated for cr]; IT grad student or instr consent
MOT 4001 - Leadership, Professionalism and Business Basics for Engineers
Credits: 2.0 [max 2.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Elements of business, environment in which technology/business operate. Classes of 15 to 20 students.
EE 8888 - Thesis Credit: Doctoral
Credits: 1.0 -24.0 [max 100.0]
Grading Basis: No Grade
Typically offered: Every Fall, Spring & Summer
Thesis credit.