Program Details : University Catalogs : University of Minnesota

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 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 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 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 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 8151 - Biomedical Electronics and Implantable Microsystems

Credits:	3.0 [max 3.0]
Typically offered:	Every Spring

This class is about bioelectronics and the synergy between electronics and biomedical applications. It discusses how to architect robust ultra-low-power electronics with applications in implantable, noninvasive, wireless, sensing, and stimulating biomedical systems. Half of the classes span feedback systems, transistor device physics, noise, and circuit-analysis techniques to provide a circuit-foundation. The other half are research papers that describe the utilization of these circuits in implantable and wearable systems. Some of these systems include cochlear implants for the deaf, brain implants for the blind and paralyzed, cardiac devices for noninvasive medical monitoring, and biomolecular sensing systems. Prerequisites: BMEn 5101 or equivalent background in bioinstrumentation and electric circuits.

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 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 8431 - Controlled Drug and Gene Delivery: Materials, Mechanisms, and Models

Credits:	4.0 [max 4.0]
Course Equivalencies:	BMEn 8431/PHM 8431
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Physical, chemical, physiological, mathematical principles underlying design of delivery systems for drugs. Small molecules, proteins, genes. Temporal controlled release. prereq: Differential equations course including partial differential equations or instr consent

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 8601 - Biomedical Engineering Seminar

Credits:	1.0 [max 1.0]
Grading Basis:	S-N or Aud
Typically offered:	Every Fall

Lectures and demonstrations of university and industry research introducing students and faculty to methods and goals of biomedical engineering.

BMEN 8602 - Biomedical Engineering Seminar

Credits:	1.0 [max 1.0]
Grading Basis:	S-N or Aud
Typically offered:	Every Spring

Lectures and demonstrations of university and industry research introducing students and faculty to methods and goals of biomedical engineering.

BIOC 5216 - Current Topics in Signal Transduction

Credits:	2.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

Mechanisms by which biological signals evoke biochemical responses.

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 5444 - Muscle

Credits:	3.0 [max 3.0]
Course Equivalencies:	BioC 5444/ Phsl 5444
Typically offered:	Every Spring

Muscle molecular structure/function and disease. Muscle regulation, ion transport, and force generation. Muscular dystrophy and heart disease. prereq: 3021 or BIOL 3021 or 4331 or BIOL 4331 or PHSL 3061 or instr consent

BIOC 6021 - Biochemistry

Credits:	3.0 [max 3.0]
Course Equivalencies:	BioC 3021/BioC 3022/BioC 4331/
Typically offered:	Every Fall, Spring & Summer

Fundamentals of biochemistry. Structure/function of proteins, nucleic acids, lipids and carbohydrates. Metabolism, regulation of metabolism. Quantitative treatments of chemical equilibria, enzyme catalysis, and bioenergetics. Chemical basis of genetic information flow. prereq: general biology, organic chemistry, instr consent; intended for MBS students

BIOC 8002 - Molecular Biology and Regulation of Biological Processes

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

Classical to current topics in molecular biology. Aspects of DNA, RNA, and protein biology. DNA replication, repair, and recombination. RNA transcription, editing, and regulation. Protein translation/modification. Technologies such as deep-sequencing micro-RNA and prions. prereq: [BMBB or MCDBG] grad student or instr consent

BIOC 8216 - Signal Transduction and Gene Expression

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall & Spring

Cell signaling, metabolic regulation in development. Procaryotic/eucaryotic systems used as models for discussion. Literature-based course. prereq: 8002 or instr consent

BMEN 5031 - Engineering Extracellular Matrices

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

This class explores the complex set of fibrous and linking proteins of tissues, namely the extracellular matrix (ECM). The ECM is crucial not only for maintaining the structure of tissues but also for guiding and maintaining cellular functions and fate processes. The purpose of the course is to become acquainted with ECM proteins and to investigate how control or manipulation of ECM proteins impacts on cell and tissue function with an emphasis on impacts for regenerative medicine. In the course of this study, we will apply fundamentals of physics, chemistry, and mathematics to make predictions, solve problems and optimize outcomes related to ECM engineering. Required prerequisites: Upper Division Undergraduate or Graduate level student standing in CSE. Recommended prerequisites: BMEn 2501, 3011/3015, 3111/3115, 3311/3315, or equivalents (introductory cell/molecular biology, biomaterials, biotransport, biomechanics).

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 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.

CGSC 8041 - Cognitive Neuroscience

Credits:	4.0 [max 4.0]
Course Equivalencies:	CgSc 8041/NSC 8041
Grading Basis:	A-F or Aud
Typically offered:	Spring Even Year

Relations between brain activity and cognitive function in mammals. Working memory, attention, decision processing, executive function, categorization, planning, sequence processing. Behavioral/physiological perspectives. Disruption of cognitive function following brain damage. Extracellular recording of single neuron activity in nonhuman primates. Functional neuroimaging/magnetoencephalography in humans. prereq: instr consent

CMB 8303 - Comparative Models of Disease

Credits:	2.0 [max 2.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

Disease processes in organ systems. Examples of animal models. Comparative medicine. Clinical relevance of problem/disease. Animal models used to study disease process/problem. Lectures. prereq: Enrollment in a biological sciences grad program or instr consent

CPMS 5101 - Introduction to Clinical Physiology and Movement Science

Credits:	3.0 [max 6.0]
Grading Basis:	A-F or Aud
Typically offered:	Periodic Fall

Overview of clinical physiology and clinical movement science. For students in such diverse fields as bioengineering, kinesiology, neuroscience, physical therapy, physiology, psychology, public health, occupational therapy.

EEB 5371 - Principles of Systematics

Credits:	3.0 [max 3.0]
Typically offered:	Fall Odd Year

Theoretical/practical procedures of biological systematics. Phylogeny reconstruction. Computer-assisted analyses, morphological and molecular approaches, species concepts/speciation, comparative methods, classification, historical biogeography, nomenclature, use/value of museums. prereq: Grad student 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

GCD 8008 - Mammalian Gene Transfer and Genome Engineering

Credits:	2.0 [max 2.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Current gene transfer and genome engineering technology. Applications of genetic modifications in animals, particularly transgenic animals and human gene therapy. prereq: instr consent

GCD 8103 - Human Histology

Credits:	5.0 [max 5.0]
Course Equivalencies:	GCD 6103/8103
Typically offered:	Every Fall

Light/electron microscopic anatomy of tissues and their organization into human organs. Emphasizes integrating structure, its relationship to function at levels from molecules to organs. Lecture, lab. prereq: Undergraduate biology, chemistry, math, and physics course; instr consent

GCD 8131 - Advanced Molecular Genetics and Genomics

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall & Spring

Literature-based course in modern molecular genetic and genomic analysis. Students will gain a deep understanding of the fundamental molecular mechanisms controlling inheritance in biological systems. Students will gain a facility in thinking critically and creatively about how genes work at cellular, organismal, and transgenerational levels. Course instruction emphasizes active-learning approaches, student presentations, and group projects. prereq: [3022 or BIOL 4003], [BIOC 3021 or BIOC 4331] or instr consent

GCD 8151 - Cellular Biochemistry and Cell Biology

Credits:	2.0 -4.0 [max 4.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

This course introduces graduate students to fundamental concepts of Biochemical Unity (Part 1) and Cell Theory (Part 2). For Part 1, we will discuss matter of life, equilibrium, entropy & law of mass action, two state systems, random walks & diffusion, rate equations of chemical reactions, and explore how they relate to regulation of biological networks (gene regulation and signal transduction). For Part 2 we will focus on properties of biological membranes, membrane trafficking, protein import & degradation, nuclear structures and their function, as well as molecular motors, cytoskeletal dynamics, and mitosis. The course assumes students have had previous undergraduate courses in cell biology, biochemistry and genetics. prereq: [[[4034 or 8121 or BioC 8002], Biol 4004] or BMBB or MCDBG grad student] or instr consent

GCD 8161 - Advanced Cell Biology and Development

Credits:	2.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

The advanced cell and developmental biology of embryos, taught through in-depth, comparative analysis of historical and current primary research articles that illustrate developmental mechanisms and experimental approaches in key invertebrate and vertebrate model organisms. prereq:[BMBB or MCDBG grad student] or [GCD 4161, [GCD 8131 or Biol 4003], Biol 4004, and GCD 4034] or instr consent

MEDC 5245 - Introduction to Drug Design

Credits:	3.0 [max 3.0]
Course Equivalencies:	Chem 5245/Phar 6245/MedC 5245
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Concepts that govern design/discovery of drugs. Physical, bioorganic, medicinal chemical principles applied to explain rational design, mechanism of action drugs. prereq: Chem

MEDC 8001 - General Principles of Medicinal Chemistry

Credits:	3.0 [max 3.0]
Course Equivalencies:	MedC 5700/MedC 8001
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Fundamental principles of molecular recognition, physiochemical properties of drugs, drug metabolism and disposition, interaction of molecules with DNA/RNA. prereq: Med chem grad student or instr consent

MEDC 8002 - General Principles of Medicinal Chemistry

Credits:	3.0 [max 3.0]
Course Equivalencies:	MedC 5710/MedC 8002
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Fundamental principles of molecular recognition, physicochemical properties of drugs, drug metabolism and disposition, interaction of molecules with DNA/RNA. prereq: Med chem grad student or instr consent

MEDC 8070 - The Chemistry and Biology of Infectious Diseases

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Periodic Fall & Spring

The objectives of this course are to provide a comprehensive overview of antimicrobial agents used in infectious diseases with an emphasis on the underlying foundational principles in chemistry and biology. Antibiotic, antifungal, and antiprotozoal agents will be covered. For each antimicrobial agent, the history, discovery, synthesis, structure-activity relationships, spectrum of activity, clinical uses, mechanism(s) of action, resistance, drug disposition properties, and adverse reactions will be discussed in great detail.

MEDC 8461 - Design of Cancer Therapeutics

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Spring Even Year

Cancer Drug Therapy is a relatively new field of medicine that has undergone many medical and societal changes over the course of the last 100 years and in particular the last 60 years. The emphasis in this course will be to familiarize the student with the basic concepts of cancer biology and to survey current advanced approaches for the development and design of small molecule, protein and cell based therapeutics for the treatment of cancer.

MEDC 8753 - MOLECULAR TARGETS OF DRUG DISCOVERY

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Fall Even Year

Structure of biological macromolecules that are targets of drugs. Techniques to accelerate directed drug discovery. Protein structure/interactions. Popular target classes. Computational tools for visualizing/analyzing protein-ligand and protein-protein interactions. Structural characterization at a level sufficient to underpin critical data evaluation. Biophysical techniques to assess weak ligand binding and suitable for fragment-based lead discovery. prereq: 5710 or 8002 or CHEM 5412 or structural biochemistry or instr consent

MEDC 8760 - Design of Peptidomimetics

Credits:	2.0 [max 2.0]
Grading Basis:	A-F or Aud
Typically offered:	Periodic Fall

Current approaches to design and synthesis of mimetics of biologically active peptides. Structural and conformational rationale used in peptidomimetic design. prereq: 5600 or instr consent

MICA 8002 - Structure, Function, and Genetics of Bacteria and Viruses

Credits:	4.0 [max 4.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Structure, function, and metabolism of microorganisms. Microbial genetics. Molecular virology. prereq: [One undergrad or grad course each in [microbiology, genetics, biochemistry]] or instr consent

MICA 8003 - Immunity and Immunopathology

Credits:	4.0 [max 4.0]
Typically offered:	Every Fall

Lymphocyte activation, signal transduction in lymphocytes, antigen receptor genetics, antigen presentation, lymphoid anatomy, adaptive immune responses to microbes, immunodeficiency, immunopathology, cytokines, transplantation, autoimmunity. prereq: Upper level undergrad immunology course or instr consent

MICA 8004 - Cellular and Cancer Biology

Credits:	4.0 [max 4.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Fundamental concepts in cellular, molecular, and genetic basis of disease. Molecular basis of inflammation and cancer metastasis. Genetic basis for inherited disorders and gene therapy. Molecular mechanisms of pathogenesis. prereq: [One undergrad or grad course each in [biochemistry, cell biology]] or instr consent

MICA 8009 - Biochemical Aspects of Normal and Abnormal Cell Growth and Cell Death

Credits:	2.0 [max 2.0]
Typically offered:	Every Spring

Aspects of mechanisms involved in growth control at level of nuclear function. Neoplasia in hormonal cancers (such as prostate cancer) and role of protein phosphorylation in normal and abnormal growth. Mechanisms of cell death via apoptosis and its implications in normal and abnormal proliferation. prereq: 8004 or [BioC 3021, Biol 4004] or instr consent

MICA 8011 - Current Topics in Immunology

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Colloquium format. In-depth reading, discussion prereq: MICA 8003 or instr consent

MLSP 5111 - Concepts of Diagnostic Microbiology

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

Investigation of pathophysiologic mechanisms of disease for medically significant human bacteria and yeast including epidemiology, pathogenesis, spectrum of disease, antimicrobial susceptibility testing and therapy. Current analytical methods and applications are discussed.

MLSP 5511 - Principles of Immunobiology

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Every Fall & Summer

Comprehensive exploration of the immune system and functions. Fundamental principles of humoral and cellular immunity. Adaptive immunity, clinical outcomes, hypersensitivity, autoimmunity, cancer, transplantation, immunotherapy, and immunity against infectious diseases. Immunologic testing methods and immune function assessment are discussed.

MPHY 5172 - Radiation Biology

Credits:	3.0 [max 3.0]
Course Equivalencies:	BPhy 5172/TRad 7172
Typically offered:	Every Fall & Spring

Effects of ionizing radiation on cells, tissues, and organisms. Biochemical/physiological bases of radiation effects. Biological rationale for radiation therapy practices. prereq: 5170 or instr consent

NEUR 5230 - Cerebrovascular Hemodynamics and Diseases I

Credits:	4.0 [max 4.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

Principles of cerebrovascular disease/pathophysiology, hemodynamics, diagnostic imaging, and endovacular devices. Bench-to-bedside experiments. Clinical trials, including design constraints and biostatistics. prereq: [[PHSL 3051 or PHSL 3063], [MATH 1271 or MATH 1371], [MATH 1272 or MATH 1372], [PHYS 1201W or PHYS 1301W], instr consent] or [grad student, [PHSL 5061 or instr consent]]

NSC 5461 - Cellular and Molecular Neuroscience

Credits:	3.0 [max 4.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Lectures by team of faculty, problem sets in important physiological concepts, discussion of original research papers. prereq: NSc grad student or instr consent

NSC 5462 - Neuroscience Principles of Drug Abuse

Credits:	2.0 [max 2.0]
Course Equivalencies:	Phcl 5462/Nsc 5462
Typically offered:	Periodic Spring

Current research on drugs of abuse, their mechanisms of action, characteristics shared by various agents, and neural systems affected by them. Offered biennially, spring semester of even-numbered years. prereq: instr consent

NSC 5540 - Survey of Biomedical Neuroscience

Credits:	2.0 [max 2.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Summer

Current topics in biomedical neuroscience, accompanied by supporting, fundamental concepts. Intensive, one week course. prereq: instr consent, intended for members of biomedical community or students with advanced scientific backgrounds

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

NSC 5661 - Behavioral Neuroscience

Credits:	2.0 [max 4.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Neural coding/representation of movement parameters. Neural mechanisms underlying higher order processes such as memorization, memory scanning, and mental rotation. Emphasizes experimental psychological studies in human subjects, single cell recording experiments in subhuman primates, and artificial neural network modeling. prereq: Grad NSc major or grad NSc minor or instr consent

NSC 8208 - Neuropsychopharmacology

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Fall Even Year

Methodologies to study relationships between drugs and biochemical, behavioral, and neurophysiological consequences. Functional biogenic amine, peptidergic, other pathways. How manipulations alter neuronal function or behavior. Feedback mechanisms, induction, inhibition. Reinforcement of, tolerance to, or dependence on drugs of abuse: stimulants, hallucinogens, depressants, opiates. Student presentations. prereq: [5212, 6112, PSY 5021, PSY 5061] or instr consent

NSC 8211 - Developmental Neurobiology

Credits:	2.0 -4.0 [max 4.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

How neuronal types develop. Emphasizes general mechanisms. Experimental data demonstrating mechanisms. prereq: Neuroscience grad student or instr consent

NSC 8221 - Neurobiology of Pain and Analgesia

Credits:	3.0 [max 3.0]
Typically offered:	Periodic Fall & Spring

Pain and analgesia. Course is triennial. prereq: instr consent

NSCI 5101 - Neurobiology I: Molecules, Cells, and Systems

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall & Spring

This course discusses the basic principles of cellular and molecular neurobiology and nervous systems. The main topics include: Organization of simple networks, neural systems and behavior; how the brain develops and the physiology and communication of neurons and glia; the molecular and genetic basis of cell organization; ion channel structure and function; the molecular basis of synaptic receptors; transduction mechanisms and second messengers; intracellular regulation of calcium; neurotransmitter systems, including excitation and inhibition, neuromodulation, system regulation and the cellular basis of learning, memory and cognition. The course is intended for students majoring in neuroscience, but is open to all students with the required prerequisites.

NSCI 5501 - Neurodegenerative Diseases, Mechanisms to Therapies

Credits:	3.0 [max 3.0]
Course Equivalencies:	Nsci 4501/Nsci 5501
Grading Basis:	A-F only
Typically offered:	Every Fall

With a rapid increase in population aging in western educated industrialized rich democratic (WEIRD) societies, neurodegenerative disorders such as Alzheimer?s disease have become an alarming health priority due to the current absence of disease-modifying therapies. The objective of this course is to acquire a fundamental appreciation for the most common degenerative disorders of the nervous system as well as to integrate central notions shared across these diseases and emerging concepts in the field.

OBIO 8012 - Basic Concepts in Skeletal Biology

Credits:	2.0 [max 2.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Cells (osteoblasts, osteoclasts, chrondrocytes) that make up skeleton. Transcription/signaling networks that regulate cell growth/differentiation. Mechanisms of bone remodeling. Regulation of bone by such agents such as hormones. Prereq Grad student or instr consent.

OBIO 8028 - Molecular Basis of Cellular and Microbial Adhesion

Credits:	2.0 [max 2.0]
Grading Basis:	A-F or Aud
Typically offered:	Spring Odd Year

Biochemical basis of adhesion phenomena. Cells of immune system, development of organs, tissue formation, bacterial colonization of the human. prereq: Dental specialist or oral research trainee or instr consent

OBIO 8050 - Evolution of Emerging Viruses

Credits:	2.0 [max 2.0]
Grading Basis:	A-F or Aud
Typically offered:	Fall Odd Year

This course is designed to provide PhD-level graduate students a knowledge base for understanding how HIV and other emerging viruses (e.g., Ebola, influenza, SARS, West Nile virus, hantavirus, hepatitis C) evolve and become public health threats. Topics for the course will focus on the biochemical, molecular, cellular, clinical, and epidemiological aspects of emerging viruses, with an emphasis on how each plays a role in virus evolution and emergence. This course will emphasize HIV as a key example of an emerging virus disease that has had a profound impact on human health. MS-level and advanced undergraduate students should register for OBIO 5050.

PHAR 5700 - Applied Fundamentals of Pharmacotherapy

Credits:	3.0 [max 3.0]
Course Equivalencies:	Phar 3700/Phar 5700
Grading Basis:	A-F only
Typically offered:	Every Fall & Spring

Pharmacotherapy, the treatment of disease through the administration of medications, is a field particularly interesting to many health care workers. This course is designed to introduce students to some of the main drug classes available for the treatment of particular diseases. Students will also learn about basic pharmacology, recognize brand and generic drug names, and explore their common uses and therapeutic classes. A basic understanding of treatment options available for common disease states will also be developed during this course. Additionally, the course develops basic proficiency in the use of drug information resources. This is a completely online course with due dates throughout the semester, though students have the option to work ahead if they choose. This course is offered each Fall, Spring, and Summer term. For more information, contact phar3700@umn.edu or 612-624-7976. Prereq: Medical terminology recommended

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 5115 - Clinical Physiology I

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Cellular mechanisms, disease states and clinical applications of excitable tissues: cellular transport, neurophysiology, skeletal muscle physiology, cardiovascular physiology. prereq: instr consent

PHSL 5116 - Clinical Physiology II

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Cellular mechanisms, disease states and clinical applications of metabolic systems: respiratory physiology, renal physiology, acid base physiology, metabolism, gastrointestinal physiology, endocrine physiology, physiology of pregnancy and labor. prereq: instr consent

PHSL 5197 - Stress Physiology

Credits:	1.0 -3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

Journal club format. Meets weekly to examine foundations of stress, historical progress, development of stress, modern stress physiology. Focus on stress-induced pathology with attention to cardiovascular, metabolic, neuroendocrine disorders. Students participating in the weekly discussion are assessed on discussion participation, completion of weekly writing assignments and quality of the presentation in the class, are eligible for 1 credit. Students completing a midterm (test) and a final project (specific aims page of an NIH RO1 grant) in addition to the criteria described above are eligible for 3 credits. Prerequisite: instructor consent is required. Graduate student standing, master students, and post-doctoral fellows (if they are eligible for credits). Undergraduate students must have taken PHSL 3061 or equivalent, and have previous laboratory research experience.

PHSL 5211 - Physiology of Inflammation in Disease

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

In this course, we will explore the latest developments in the field of inflammation-mediated chronic diseases. The students will learn basic concepts of immunity and inflammation and the mechanisms by which non-infectious inflammatory processes mediate chronic disease. Instructor consent is required. Courses in physiology, such as PHSL3051, 3061, and Microbiology and Immunology, such as MICB 4131, are recommended but not required.

PHSL 5444 - Muscle

Credits:	3.0 [max 3.0]
Course Equivalencies:	BioC 5444/ Phsl 5444
Typically offered:	Every Spring

Muscle molecular structure/function and disease. Muscle regulation, ion transport, and force generation. Muscular dystrophy and heart disease. prereq: PHSL 3061 or PHSL 5061 or BioC 3021, BIOL 3021 or BIOL 4331 or instr consent

PHSL 5510 - Advanced Cardiac Physiology and Anatomy

Credits:	2.0 -3.0 [max 3.0]
Typically offered:	Every Spring

Fundamental concepts, advanced topics related to clinical/biomedical cardiac physiology. Lectures, laboratories, workshops, anatomical dissections. Intense, one week course. prereq: instr consent

PHSL 5525 - Anatomy and Physiology of the Pelvis and Urinary System

Credits:	1.0 -2.0 [max 2.0]
Course Equivalencies:	Anat 5525/Phsl 5525
Grading Basis:	A-F only
Typically offered:	Every Spring

Two-day intensive course. Pelvis, perineum, and urinary system with cadaveric dissection. Structure/function of pelvic and urinary organs, including common dysfunction and pathophysiology. Laboratory dissections, including kidneys, ureters, urinary bladder, pelvic viscera and perineum (male or female), pelvic floor, vascular and nervous structures. Grand rounds section. prereq: One undergrad anatomy course, one undergrad physiology course, instr consent

PSY 5015 - Cognition, Computation, and Brain

Credits:	3.0 [max 3.0]
Typically offered:	Spring Even Year

Human cognitive abilities (perception, memory, attention) from different perspectives (e.g., cognitive psychological approach, cognitive neuroscience approach). prereq: [Honors or grad] or [[jr or sr], [3011 or 3031 or 3051 or 3061]] or instr consent

PSY 5062 - Cognitive Neuropsychology

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall

Consequences of different types of brain damage on human perception/cognition. Neural mechanisms of normal perceptual/cognitive functions. Vision/attention disorders, split brain, language deficits, memory disorders, central planning deficits. Emphasizes function/phenomenology. Minimal amount of brain anatomy. prereq: Grad or [[jr or sr], [3011 or 3031 or 3051 or 3061]] or instr consent

PSY 8041 - Proseminar in Perception

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Fall Odd Year

Seminar. Advanced topics in auditory and visual perception. Lecture, discussion, and student-led presentations of research papers on core topics of the peripheral visual and auditory systems, cortical representations, behavioral and brain-imaging methods, and computational approaches to understanding/simulating perception. prereq: Psy grad student or instr consent

RSC 5200 - Introduction to Neuromodulation

Credits:	1.0 -3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Fall Even Year

This course will provide training in the theory, biophysics and evidence-based application of non-invasive magnetic and electric brain stimulation in humans. Course content will be delivered in three modules: (1) safety and administration of non-invasive brain stimulation, (2) neuromodulation methods, and (3) advanced assessment and modeling techniques. All registered students must take module #1. Testing methods will include various methods to assess intracortical, transcallosal and interhemispheric excitability. Neuromodulation methods presented will include non-invasive and invasive forms of brain stimulation. Hands-on instruction and laboratory applications will be provided for cortical excitability testing using transcranial magnetic stimulation (TMS) as well as for other non-invasive forms of brain stimulation. Those enrolled will both administer and receive non-invasive brain stimulation and will be asked to sign a consent form. Specific safety exclusion criteria for receiving non-invasive brain stimulation exist and enrollees who have questions should contact the Division of Rehabilitation Science.

RSC 5231 - Clinical Biomechanics

Credits:	2.0 -5.0 [max 5.0]
Course Equivalencies:	PT 6231/RSC 5231
Grading Basis:	A-F only
Typically offered:	Every Fall

Biomechanics. Internal/external forces/structures responsible for normal/abnormal human movement. Joint and tissue mechanics, muscle function, task analysis, and gait mechanics. Lecture and lab practice. prereq: concurrent registration is required (or allowed) in PT 6231, general physics, [intro or short] calculus, anatomy; intensive anatomy course in human cadaver dissection recommended

RSC 5281 - Physiology for Physical Rehabilitation

Credits:	2.0 -4.0 [max 4.0]
Course Equivalencies:	PT 6281/RSC 5281
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

This course provides an in-depth presentation of fundamental concepts in tissue and organ system physiology as it relate to general health, aging, and physical exercise. Emphasis is on the following systems: muscle, bone & connective tissue, endocrine, immune, renal, gi, and hematology. Influence of aging on these systems will be addressed as well. prereq: Rehabilitation Science grad student

RSC 5402 - The Shoulder in Sports Rehabilitation Science

Credits:	3.0 [max 3.0]
Course Equivalencies:	PT 6402/RSC 5402
Grading Basis:	A-F or Aud
Typically offered:	Every Spring & Summer

A three-credit online course for students who are interested in investigating the biomechanical and epidemiological aspects of the shoulder in athletics. The course will explore the unique demands placed on the shoulder in sports that involve throwing, swimming, swinging, and bodily impacts. The course begins with an investigation into sport-specific biomechanics, pathomechanics, and epidemiology and progresses to applied problem solving for rehabilitation and research scenarios. prereq: (1) an undergraduate or graduate human anatomy course and (2) an undergraduate or graduate biomechanics course. It is recommended, but not required, you have an anatomy course including a detailed shoulder anatomy section and a biomechanics course including a detailed shoulder biomechanics section. Consent from course instructor or Rehabilitation Science graduate program is required.

RSC 8282 - Problems in Human Movement

Credits:	4.0 [max 4.0]
Prerequisites:	[Rehabilitation science student or program permission], #
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Fundamental principles of neurophysiology, neurology, motor control, and motor learning as a basis for therapeutic intervention in motor dysfunction. prereq: [Rehabilitation science student or program permission], instr consent

SCB 8181 - Stem Cell Biology

Credits:	3.0 [max 3.0]
Course Equivalencies:	GCD 8181/SCB 8181
Typically offered:	Every Fall

Stem cell research and its applications. Critical analysis, written summaries/critiques, oral presentations. prereq: [[GCD 4034], [GCD 4161]] or equiv or instr consent

SLHS 5605 - Language and Cognitive Disorders in Adults

Credits:	3.0 [max 3.0]
Typically offered:	Periodic Fall & Spring

Acquired cognitive and communicative disorders in the adult population specifically including: stroke/aphasia, right hemisphere dysfunction, traumatic brain injury, and dementia. Consideration of neurological substrates, disorder symptomology, assessment, clinical intervention, and functional impact across the lifespan and amongst diverse populations. prereq: [3302, 4301] or [CDis 3302, CDis 4301] or instr consent

SLHS 5802 - Hearing Aids I

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall

Survey of modern hearing aids including history of development, electroacoustic functions, clinic and laboratory measurement techniques, sound field acoustics, techniques for selection. prereq: [[3305, 4801] or [CDIS 3305, CDIS 4801], SLHS grad] or instr consent

SLHS 5806 - Auditory Disorders in Children

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

In this course students learn about assessing hearing and listening difficulties in children ?beyond the audiogram?, as well as the pediatric-specific considerations for intervention and management of identified hearing difficulties. This course covers the anatomy and physiology of the central auditory pathway, assessments to evaluate auditory disorders and processing skills, and techniques to address auditory processing weaknesses and disorders in children. Additional topics include normal and disordered auditory processing abilities, current and historical theories and controversies surrounding auditory assessment beyond the audiogram, and advances in the assessment and management of childhood hearing disorders. prereq: [4802 or CDIS 4802, SLHS grad] or instr consent

SLHS 8802 - Hearing Aids II

Credits:	3.0 [max 3.0]
Typically offered:	Every Spring

Instrumentation and methods for fitting and evaluating personal hearing aids; ear impression techniques and materials; repair and modification of hearing aids. prereq: 5802 or Cdis 5802 or 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 5451 - Optimal Estimation

Credits:	3.0 [max 3.0]
Course Equivalencies:	AEM 5451/EE 5251
Typically offered:	Fall Even Year

Basic probability theory. Batch/recursive least squares estimation. Filtering of linear/non-linear systems using Kalman and extended Kalman filters. Applications to sensor fusion, fault detection, and system identification. prereq: [[MATH 2243 or STAT 3021 or equiv], [4321 or EE 4231 or ME 5281 or equiv]] or instr consent

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 8201 - Fluid Mechanics I

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall

Mathematical and physical principles governing the motion of fluids. Kinematic, dynamic, and thermodynamic properties of fluids; stress and deformation; equations of motion; analysis of rotational and irrotational inviscid incompressible flow; two-dimensional and three-dimensional potential flow. prereq: 4201 or equiv, Math 2263 or equiv

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 8233 - Multi-phase Flows: Fundamentals, Measurement, and Modeling

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Spring Even Year

Introduction to fluid flows with multiple interacting phases, with emphasis on cases in which a dispersed phase is carried by a continuous one. Droplet dynamics, bubbly flows and bubble-induced fluctuations, particle-turbulence interaction. Fundamentals of measurement techniques and modeling approaches. Elements of rheology for complex and active fluids.

AEM 8511 - Advanced Topics in Continuum Mechanics

Credits:	3.0 [max 6.0]
Grading Basis:	A-F or Aud
Typically offered:	Periodic Fall & Spring

Constitutive equations; invariance and thermodynamic restrictions. Nonlinear elasticity theory; exact solutions, minimization, stability. Non-Newtonian fluids; viscometric flows, viscometric functions, normal stress. Other topics may include reactive and/or nonreactive mixtures, nonlinear plasticity, and deformable electromagnetic continua. prereq: 5501 or instr consent

AEM 8531 - Fracture Mechanics

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Periodic Fall & Spring

Theories of mechanical breakdown. Kinetic rate theories and instability considerations; formation of equilibrium cracks and circular crack propagation under pulses; statistical aspects of strength and fracture of micromolecular systems; time and temperature dependency in fracture problems and instability of compressed material systems. prereq: 5503 or instr consent

AEM 8551 - Multiscale Methods for Bridging Length and Time Scales

Credits:	3.0 [max 3.0]
Course Equivalencies:	AEM 8551/SCIC 8551
Prerequisites:	Basic knowledge of [continuum mechanics, atomic forces], familiarity with partial differential equations, grad student in [engineering or mathematics or physics]
Grading Basis:	A-F or Aud
Typically offered:	Periodic Spring

Classical/emerging techniques for bridging length/time scales. Nonlinear thermoelasticity, viscous fluids, and micromagnetics from macro/atomic viewpoints. Statistical mechanics, kinetic theory of gases, weak convergence methods, quasicontinuum, effective Hamiltonians, MD, new methods for bridging time scales. prereq: Basic knowledge of [continuum mechanics, atomic forces], familiarity with partial differential equations, grad student in [engineering or mathematics or physics]

BBE 5301 - 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.

BIOC 5351 - Protein Engineering

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Key properties of enzymes/molecular basis, computer modeling strategies, mutagenesis strategies to create protein variants, expression/screening of protein variants. Evaluate research papers, identify unsolved practical/theoretical problems, plan protein engineering experiment.

BIOC 5352 - Biotechnology and Bioengineering for Biochemists

Credits:	3.0 [max 3.0]
Course Equivalencies:	BioC 5352/MicB 5352
Grading Basis:	A-F or Aud
Typically offered:	Periodic Spring

Protein biotechnology. Microorganisms used as hosts for protein expression, protein expression, and engineering methods. Production of enzymes of industrial interest. Applications of protein biotechnology in bioelectronics. Formulation of therapeutic biopharmaceuticals. Recommended prerequisites: Biochemistry (BiOC 3021 or 3022 or 4331) and Microbiology MICB 3301

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

BIOC 8005 - Biochemistry: Structure and Catalysis

Credits:	2.0 [max 2.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Protein structure, methods to determine structure, protein folding, forces stabilizing macromolecular structure, protein engineering, design. Dynamic properties of proteins/enzymes, enzyme substrate complexes, mechanism of enzyme catalysis.

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 5361 - 3D Bioprinting

Credits:	2.0 [max 2.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

3D Bioprinting has recently emerged as a new biofabrication technology that merges many engineering fields (eg. BME, MechE, ChemE) with other disciplines such as Materials Science, Stem Cell Biology, Physiology, Surgery and Pharmacology. This course serves as an introduction to the field and how its disciplines interface, while providing the student with knowledge of many of the most common bioprinting methods and applications being developed today through lectures by experts in the field (academia and industry) as well as hands-on lab exercises in the UMN 3D Bioprinting Facility.

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 5601 - Cardiovascular Devices

Credits:	1.0 [max 1.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Design of cardiovascular devices with experts from local medtech companies. Discussion of clinical need, the generic design (emphasizing use of engineering principles), typical testing and validation methods, and major limitations of the available devices. Design, analysis, and testing of these and related devices. prereq: BMEN 3011, 3111, 3211, or equivalents with instr consent

BMEN 5910 - Special Topics in Biomedical Engineering

Credits:	3.0 [max 6.0]
Typically offered:	Periodic Fall & Spring

Special topics in biomedical engineering.

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 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 8151 - Biomedical Electronics and Implantable Microsystems

Credits:	3.0 [max 3.0]
Typically offered:	Every Spring

This class is about bioelectronics and the synergy between electronics and biomedical applications. It discusses how to architect robust ultra-low-power electronics with applications in implantable, noninvasive, wireless, sensing, and stimulating biomedical systems. Half of the classes span feedback systems, transistor device physics, noise, and circuit-analysis techniques to provide a circuit-foundation. The other half are research papers that describe the utilization of these circuits in implantable and wearable systems. Some of these systems include cochlear implants for the deaf, brain implants for the blind and paralyzed, cardiac devices for noninvasive medical monitoring, and biomolecular sensing systems. Prerequisites: BMEn 5101 or equivalent background in bioinstrumentation and electric circuits.

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 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 8431 - Controlled Drug and Gene Delivery: Materials, Mechanisms, and Models

Credits:	4.0 [max 4.0]
Course Equivalencies:	BMEn 8431/PHM 8431
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Physical, chemical, physiological, mathematical principles underlying design of delivery systems for drugs. Small molecules, proteins, genes. Temporal controlled release. prereq: Differential equations course including partial differential equations or instr consent

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.

CEGE 8401 - Fundamentals of Finite Element Method

Credits:	3.0 [max 3.0]
Prerequisites:	4411 or #
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Elements of calculus of variations; weak and strong formulations of linear continuum and structural problems. Isoparametric elements and numerical integration. Basic concepts of error analysis and convergence. Analysis of plates and shells. Introduction to mixed methods and time dependent problems. prereq: 4411 or instr consent

CHEM 8021 - Computational Chemistry

Credits:	4.0 [max 4.0]
Typically offered:	Every Spring

Modern theoretical methods used in study of molecular structure, bonding, reactivity. Concepts/practical applications. Determination of spectra, relationship to experimental techniques. Molecular mechanics. Critical assessment of reliability of methods. prereq: 4502 or equiv

CHEM 8151 - Analytical Separations and Chemical Equilibria

Credits:	4.0 [max 4.0]
Typically offered:	Every Fall & Spring

Advanced treatment of principles of analytical chemistry, chemical equilibria, and dynamics. Chromotographic and other modern analytical scale separation techniques. Emphasizes column dynamics and retention mechanisms. prereq: instr consent

CHEM 8157 - Bioanalytical Chemistry

Credits:	4.0 [max 4.0]
Grading Basis:	A-F or Aud
Typically offered:	Periodic Spring

Theory and practical aspects of analytical methods used in determination/characterization of biologically important materials. Enzymatic/kinetic methods in study of proteins, carbohydrates, lipids, and nucleic acids.

CHEM 8411 - Introduction to Chemical Biology

Credits:	4.0 [max 4.0]
Typically offered:	Every Fall

Chemistry of amino acids, peptides, proteins, lipids, carbohydrates, and nucleic acids. Structure, nomenclature, synthesis, and reactivity. Overview of techniques used to characterize these biomolecules. prereq: 2302 or equiv

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 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 8201 - Applied Math

Credits:	3.0 [max 3.0]
Course Equivalencies:	ChEn 4701/ChEn 8201
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Integrated approach to solving linear mathematical problems. Linear algebraic equations. Linear ordinary and partial differential equations using theoretical/numerical analysis based on linear operator theory. prereq: Chemical engineering grad student or instr consent

CHEN 8221 - Synthetic Polymer Chemistry

Credits:	4.0 [max 4.0]
Course Equivalencies:	ChEn 8221/MatS 8221/Chem 8221
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Condensation, radical, ionic, emulsion, ring-opening, metal-catalyzed polymerizations. Chain conformation, solution thermodynamics, molecular weight characterization, physical properties. prereq: [Undergrad organic chemistry course, undergrad physical chemistry course] or instr consent

CHEN 8301 - Physical Rate Processes I: Transport

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Periodic Fall & Spring

Survey of mass transfer, dilute, and concentrated diffusion. Brownian motion. Diffusion coefficients in polymers, of electrolytes, and at critical points. Multicomponent diffusion. Mass transfer correlations/predictions. Mass transfer coupled with chemical reaction.

CHEN 8402 - Statistical Thermodynamics and Kinetics

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Introduction to statistical mechanical description of equilibrium and non-equilibrium properties of matter. Emphasizes fluids, classical statistical mechanics. prereq: Chemical engineering grad student or instr 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

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 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 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 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 5527 - Deep Learning: Models, Computation, and Applications

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall

This course introduces the basic ingredients of deep learning, describes effective models and computational principles, and samples important applications. Topics include universal approximation theorems, basics of numerical optimization, auto-differentiation, convolution neural networks, recurrent neural networks, generative neural networks, representation learning, and deep reinforcement learning. Prerequisite: CSCI 5521 or equivalent Maturity in linear algebra, calculus, and basic probability is assumed. Familiarity with Python is necessary to complete the homework assignments and final project.

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 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 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

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 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 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 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 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 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 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 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 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 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 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

HINF 5430 - Foundations of Health Informatics I

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall & Spring

An introductory survey of health informatics, focusing on foundational concepts. Topics covered include: conceptualizations of data, information, and knowledge; current terminologies, coding, and classification systems for medical information; ethics, privacy, and security; systems analysis, process and data modeling; human-computer interaction and data visualization. Lectures, readings, and exercises highlight the intersections of these topics with electronic health record systems and other health information technology. prereq: Junior, senior, grad student, professional student, or instr consent

HINF 5431 - Foundations of Health Informatics II

Credits:	3.0 [max 3.0]
Typically offered:	Every Spring

An introductory survey of health informatics, focusing on applications of informatics concepts and technologies. Topics covered include: health informatics research, literature, and evaluation; precision medicine; decision models; computerized decision support systems; data mining, natural language processing, social media, rule-based system, and other emerging technologies for supporting 'Big Data' applications; security for health care information handling. Lectures, readings, and exercises highlight the intersections of these topics with current information technology for clinical care and research. prereq: Junior, senior, grad student, professional student, or instr consent

HINF 5502 - Python Programming Essentials for the Health Sciences

Credits:	1.0 [max 1.0]
Grading Basis:	S-N or Aud
Typically offered:	Every Fall & Spring

Computer programming essentials for health sciences/health care applications using Python 3. Intended for students with limited programming background, or students wishing to obtain proficiency in Python programming language. prereq: Junior or senior or grad student or professional student or instr consent

HINF 8440 - Foundations of Translational Bioinformatics Lab

Credits:	2.0 [max 2.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Translational bioinformatics deals with the assaying, computational analysis and knowledge-based interpretation of complex molecular data to better understand, prevent, diagnose and treat disease. This course emphasizes deep DNA sequencing methods that have persistent impact on research related to disease diagnosis and treatment. The course covers sequence analysis, applications to genome sequences, and sequence-function analysis, analysis of modern genomic data, sequence analysis for gene expression/functional genomics analysis, and gene mapping/applied population genetics. Prerequisites: MS, PhD, or MD/PhD student interested in translational bioinformatics

HUMF 5001 - Foundations of Human Factors/Ergonomics

Credits:	3.0 [max 3.0]
Course Equivalencies:	HumF/Kin 5001
Grading Basis:	A-F or Aud
Typically offered:	Periodic Fall

Variability in human performance influenced by interaction with designs of machines/tools, computers/software, complex technological systems, jobs/working conditions, organizations, sociotechnical institutions. Conceptual, empirical, practical aspects of human factors/ergonomics. prereq: Grad HumF major or minor or instr consent

HUMF 5211 - Human Factors and Work Analysis

Credits:	4.0 [max 4.0]
Course Equivalencies:	HumF 5211/IE 5511/ME 5211
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Human factors engineering (ergonomics), methods engineering, work measurement. Displays, controls, instrument layout, supervisory control. Anthropometry, work physiology, biomechanics. Noise, illumination, toxicology. Operations analysis, motion study, time standards.

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 5511 - Human Factors and Work Analysis

Credits:	4.0 [max 4.0]
Course Equivalencies:	HumF 5211/IE 5511/ME 5211
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Human factors engineering (ergonomics), methods engineering, and work measurement. Human-machine interface: displays, controls, instrument layout, and supervisory control. Anthropometry, work physiology and biomechanics. Work environmental factors: noise, illumination, toxicology. Methods engineering, including operations analysis, motion study, and time standards. prereq: Upper div CSE or grad student

IE 5522 - Quality Engineering and Reliability

Credits:	4.0 [max 4.0]
Course Equivalencies:	IE 3522/IE 5522
Typically offered:	Periodic Fall & Spring

Quality engineering/management, economics of quality, statistical process control design of experiments, reliability, maintainability, availability. prereq: [4521 or equiv], [upper div or grad student or CNR]

IE 5541 - Project Management

Credits:	4.0 [max 4.0]
Course Equivalencies:	IE 4541/IE 5541
Grading Basis:	A-F only
Typically offered:	Every Fall & Spring

Introduction to engineering project management. Analytical methods of selecting, organizing, budgeting, scheduling, and controlling projects, including risk management, team leadership, and program management. prereq: Upper div or grad student

IE 5545 - Decision Analysis

Credits:	4.0 [max 4.0]
Typically offered:	Periodic Fall & Spring

Single-person and group decision problems. Structuring of decision problems arising in personal, business, and public policy contexts. Decision-making under uncertainty, value of information, games of complete information and Nash equilibrium, Bayesian games, group decision-making and distributed consensus, basics of mechanism design. prereq: 3521 or equiv

IE 5553 - Simulation

Credits:	4.0 [max 4.0]
Course Equivalencies:	IE 3553/IE 5553
Typically offered:	Periodic Fall & Spring

Discrete event simulation. Using integrated simulation/animation environment to create, analyze, and evaluate realistic models for various industry settings, including manufacturing/service operations and systems engineering. Experimental design for simulation. Selecting input distributions, evaluating simulation output. prereq: Upper div or grad student; familiarity with probability/statistics recommended

IE 8564 - Optimization for Machine Learning

Credits:	4.0 [max 4.0]
Typically offered:	Every Fall

Machine learning has been widely used in many areas such as computer vision, search engines, speech recognition, robotics, recommender systems, bioinformatics, social networks, and finance. It has become an important tool in prediction and data analysis. This course provides a comprehensive overview of important optimization models for machine learning. It also systematically provides a theoretical and computational study on various optimization methods for solving these models and more general problems.

KIN 5001 - Foundations of Human Factors/Ergonomics

Credits:	3.0 [max 3.0]
Course Equivalencies:	HumF/Kin 5001
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Variability in human performance as influenced by interaction with designs of machines and tools, computers and software, complex technological systems, jobs and working conditions, organizations, and sociotechnical institutions. Emphasizes conceptual, empirical, practical aspects of human factors/ergonomic science.

KIN 5643 - Applied Motion Capture and Movement Analysis Technology

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

Course provides students with the knowledge and tools to effectively analyze human movement patterns in a wide variety of field-based settings, such as assessing sport skill performance or measuring movement deficits after injury. Students will comprehend the basic, underlying components of movement and movement deficits. It is strongly suggested students have taken Physics, Biomechanics, and Human Anatomy. Credit will not be received if taken KIN 5720: Special Topics in Kinesiology with the topic title, Sport Movement Analysis.

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 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 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 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 8202 - General Algebra

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Classical field theory through Galois theory, including solvable equations. Symmetric, Hermitian, orthogonal, and unitary form. Tensor and exterior algebras. Basic Wedderburn theory of rings; basic representation theory of groups. prereq: 8201 or instr consent

MATH 8253 - Algebraic Geometry

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Periodic Fall

Curves, surfaces, projective space, affine and projective varieties. Rational maps. Blowing-up points. Zariski topology. Irreducible varieties, divisors. prereq: 8202 or instr consent

MATH 8441 - Numerical Analysis and Scientific Computing

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall

Approximation of functions, numerical integration. Numerical methods for elliptic partial differential equations, including finite element methods, finite difference methods, and spectral methods. Grid generation. prereq: [4xxx analysis, 4xxx applied linear algebra] or instr consent

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 8002 - Thermodynamics and Kinetics

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

First three laws of thermodynamics, free energy, equilibrium constants, fugacity and activity relationships, solution models, order-disorder transitions, phase transitions. Elementary statistical mechanics. Applications to materials systems, including surface energies, multicomponent equilibria, reaction kinetics, mass transport, diffusion.

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

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 5341 - Case Studies in Thermal Engineering and Design

Credits:	4.0 [max 4.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall & Spring

Characteristics of applied heat transfer problems. Nature of problem specification, incompleteness of needed knowledge base, accuracy issues. Categories of applied heat transfer problems. prereq: 3333, CSE upper div 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 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 8341 - Conduction

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Advanced understanding/application of conduction/diffusion to heat/mass transfer problems. Solving ordinary/partial differential equations related to physics of diffusion. Special topics in numerical microscale heat transfer. prereq: Undergrad class in heat transfer or instr consent

ME 8342 - Convection

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Heat transfer in fluids flowing around bodies and in tubes/ducts. Forced/natural convection. Laminar/turbulent flow regimes. Turbulent transport and modeling. High-speed flows, viscous dissipation, variable property effects. Application to heat exchange devices. Convective mass transfer. prereq: Grad level course on fundamentals of fluid mechanics that has a substantial component on viscous flows or instr consent

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

ME 8345 - Computational Heat Transfer and Fluid Flow

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall & Spring

Finite volume method for solution of governing equations for heat transfer and fluid flow. Mathematical models of turbulence. Construction of general computer program. Practical applications. prereq: CSE grad student

ME 8390 - Advanced Topics in the Thermal Sciences : Biostabilization in Biomedicine, and Biotechnology

Credits:	1.0 -3.0 [max 18.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Topics vary according to instructor.

MPHY 5040 - Introduction to Medical Physics

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

Interactions and energy deposition by ionizing radiation in matter; medical imaging; radiation therapy physics and related radiation safety topics.

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 5178 - Physical Principles of Magnetic Resonance Imaging

Credits:	3.0 [max 3.0]
Typically offered:	Spring Even Year

Magnetic resonance imaging physics, spatial selection and encoding, imaging hardware and system engineering. Imaging sequences, signal-to-noise, and contrast.

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

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

OBIO 8027 - Biomaterials in Regenerative Dentistry

Credits:	2.0 [max 2.0]
Grading Basis:	A-F or Aud
Typically offered:	Fall Odd Year

Describes most modern research strategies that are being developed by interdisciplinary groups to obtain revolutionary materials for its use in tissue engineering and regenerative medicine. The central role of biotechnology, nanotechnology, and biomimetics in these research strategies is highlighted. Focus on dental applications is provided. prereq: Dental specialist or oral research trainee or instr consent

PDES 5704 - Computer-Aided Design Methods

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

This class provides an overview of how to make high-quality digital computer-based models of existing and conceptual products and interactions. Students will learn Adobe Photoshop, Adobe Illustrator, and Axure for two-dimensional design and digital prototyping. Students will also learn SolidWorks and KeyShot for three-dimensional solid modeling and rendering. prereq: Senior or grad student

PHM 8431 - Controlled Drug and Gene Delivery: Materials, Mechanisms, and Models

Credits:	4.0 [max 4.0]
Course Equivalencies:	BMEn 8431/PHM 8431
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Physical, chemical, physiological, cell biological, mathematical principles underlying design of delivery systems for drugs. Small molecules, proteins, genes. prereq: Differential equations course including introduction to partial differential equations or instr consent

PHSL 5221 - Systems and Computational Physiology

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

Physiological processes can involve a complex level of interactions that can be challenging to understand based on intuition alone. Quantitative and computational approaches can be used to help us better understand the mechanisms regulating such complex processes, both in healthy and pathological conditions. In this course, students will be introduced to current methods from systems biology, computational biology, and artificial intelligence to better understand human physiology. We will discuss mathematical approaches to model biological interactions that describe fundamental physiological concepts such as feedback and homeostasis that operate across biological scales, from intracellular enzymes to organ regulation. We will apply these approaches to understand a range of physiological systems, including hormone secretion, circadian rhythms, and inflammation. We will also introduce students to machine learning and deep learning methods, and discuss how these computational approaches are being applied in the areas of clinical physiology and biomedical imaging.

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

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

PSY 5065 - Functional Imaging: Hands-on Training

Credits:	3.0 [max 3.0]
Typically offered:	Every Spring

Basic neuroimaging techniques/functional magnetic resonance imaging (fMRI). First half of semester covers basic physical principles. Second half students design/execute fMRI experiment on Siemens 3 Tesla scanner. prereq: [3801 or equiv], [3061 or NSCI 3101], instr consent

PUBH 6450 - Biostatistics I

Credits:	4.0 [max 4.0]
Grading Basis:	A-F only
Typically offered:	Every Fall & Spring

This course will cover the fundamental concepts of exploratory data analysis and statistical inference for univariate and bivariate data, including: ? study design and sampling methods, ? descriptive and graphical summaries, ? random variables and their distributions, ? interval estimation, ? hypothesis testing, ? relevant nonparametric methods, ? simple regression/correlation, and ? introduction to multiple regression. There will be a focus on analyzing data using statistical programming software and on communicating the results in short reports. Health science examples from the research literature will be used throughout the course. prereq: [College-level algebra, health sciences grad student] or instr consent

PUBH 6451 - Biostatistics II

Credits:	4.0 [max 4.0]
Typically offered:	Every Fall & Spring

This course will cover more advanced aspects of statistical analysis methods with a focus on statistical modeling, including: ? two-way ANOVA, ? multiple linear regression, ? logistic regression, ? Poisson regression, ? log binomial and ordinal regression, ? survival analysis methods, including Kaplan-Meier analysis and proportional hazards (Cox) regression, ? power and sample size, and ? survey sampling and analysis. There will be a focus on analyzing data using statistical programming software and on communicating the results in short reports. Health science examples from the research literature will be used throughout the course. prereq: [PubH 6450 with grade of at least B, health sciences grad student] or instr consent

PUBH 7440 - Introduction to Bayesian Analysis

Credits:	3.0 [max 3.0]
Typically offered:	Every Spring

Introduction to Bayesian methods. Comparison with traditional frequentist methods. Emphasizes data analysis via modern computing methods: Gibbs sampler, WinBUGS software package. prereq: [[7401 or STAT 5101 or equiv], [public health MPH or biostatistics or statistics] grad student] or instr consent

PUBH 7461 - Exploring and Visualizing Data in R

Credits:	2.0 [max 2.0]
Typically offered:	Every Fall

This course is intended for students, both within and outside the School of Public Health, who want to learn how to manipulate data, perform simple statistical analyses, and prepare basic visualizations using the statistical software R. While the tools and techniques taught will be generic, many of the examples will be drawn from biomedicine and public health.

PUBH 7475 - Statistical Learning and Data Mining

Credits:	3.0 [max 3.0]
Typically offered:	Periodic Spring

Various statistical techniques for extracting useful information (i.e., learning) from data. Linear discriminant analysis, tree-structured classifiers, feed-forward neural networks, support vector machines, other nonparametric methods, classifier ensembles, unsupervised learning. prereq: [[[6450, 6452] or equiv], programming backgroud in [FORTRAN or C/C++ or JAVA or Splus/R]] or instr consent; 2nd yr MS recommended

RSC 5135 - Advanced Biomechanics I: Kinematics

Credits:	3.0 [max 3.0]
Course Equivalencies:	RSc 5135/RSc 8135
Grading Basis:	A-F or Aud
Typically offered:	Fall Odd Year

How to describe/measure movement. Basic/applied biomechanics, pathokinesiology, and rehabilitation literature. Lecture, lab, seminar discussion. Meets with RSC 8135. prereq: instr consent

RSC 5235 - Advanced Biomechanics II: Kinetics

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Spring Even Year

Forces that create human motion and are produced within body as a result. Measuring human motion. Clinical movement assessment, Exercise, sport, and activities of daily living. Two-dimensional rigid body dynamics models, forward/inverse dynamics solutions, hypotheses to describe whole body/joint kinetics. Lectures, lab, discussion. prereq: 5135 or equiv or instr consent

RSC 5841 - Applied Data Acquisition and Processing

Credits:	3.0 [max 4.0]
Grading Basis:	A-F or Aud
Typically offered:	Spring Odd Year

This course will introduce students to collecting and processing biomedical time series data. Students will gain experience using data acquisition hardware common in many laboratories, as well as related software for acquisition of the data and digital signal processing. Data sources will include electromyography (EMG), wearable sensors, motion capture, and data from other systems based on the background and interests of students in the class. The overall goal of this course is to provide students with the necessary, fundamental skills to run a successful experiment, troubleshoot errors, and produce high quality data sets. prereq: prefer students to have completed general physics, introductory of short calculus

RSC 8135 - Human Kinematics

Credits:	3.0 [max 3.0]
Course Equivalencies:	RSc 5135/RSc 8135
Grading Basis:	A-F or Aud
Typically offered:	Fall Odd Year

How to describe/measure movement. Basic/applied biomechanics, pathokinesiology, and rehabilitation literature. Lecture, lab, seminar discussion. Meets in conjunction with RSC 5135. prereq: [Rehabilitation science student or program permission], instr consent

RSC 8235 - Human Kinetics

Credits:	3.0 [max 3.0]
Course Equivalencies:	RSC 5235/RSC 8235
Grading Basis:	A-F or Aud
Typically offered:	Spring Even Year

Forces that create human motion or are produced within body as a result of motion. Measuring kinetics of motion. Clinical movement assessment. Measuring/analyzing exercise, sport, and activities for transfer of forces within body. Two-dimensional rigid body dynamics. Forward/inverse dynamics. Hypotheses for whole body/joint kinetics. Lectures, lab experiments, discussion. Meets with RSC 5235. prereq: [5135 or equiv] or instr consent

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 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.

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

BTHX 5100 - Introduction to Clinical Ethics

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall & Spring

Healthcare is full of gray areas, high stakes situations, and tensions between personal and professional values. This course explores the moral nature of the healthcare professions and common values-based conflicts in clinical practice. By examining everyday cases, exploring current issues in healthcare, and developing habits of reflective practice, learners will have the opportunity to recognize and respond to moral uncertainties that arise in the interprofessional clinical environment. The course presents practical knowledge and skills needed for ethics deliberation and decision making. This is a blended instruction course where students can expect a majority of sessions held in-person and occasional online sessions.

BTHX 5120 - Dying in Contemporary Medical Culture

Credits:	2.0 [max 2.0]
Typically offered:	Every Fall

Examines practices of dying and death in contemporary U.S. culture, moral problems associated with these practices, possible solutions, and practical applications. Readings will consist of cultural critiques, bioethics literature, and empirical research.

BTHX 5210 - Ethics of Human Subjects Research

Credits:	3.0 [max 3.0]
Typically offered:	Fall Even Year

Issues in ethics of human subjects research. prereq: Grad student or instr consent

BTHX 5300 - Foundations of Bioethics

Credits:	3.0 [max 3.0]
Typically offered:	Every Spring

Overview of major contemporary frameworks used to approach ethical issues in bioethics. prereq: Grad student or instr consent

BTHX 5325 - Biomedical Ethics

Credits:	3.0 [max 3.0]
Course Equivalencies:	Bthx 5325/Phil 5325
Typically offered:	Every Fall

This online course examines contemporary issues in bioethics, focusing on practical issues that arise in clinical care, public health, and health policy settings. The course also introduces conceptual frameworks and methods to analyze these issues, though the emphasis will be on challenges faced by patients and their loved ones, health professionals, and policy makers, not on ethical theory. To fully understand and evaluate these complex issues, it is critical that we consider them from a diversity of perspectives. Hence, we will spend most of our time in class discussion, openly and respectfully listening to and engaging with each other in interdisciplinary/interprofessional conversation. Class meetings will be fully online via Zoom; no in-person meetings will be required. This course has been approved for Interprofessional Education (IPE) credit for health professions students. prereq: Jr or sr or grad student or instr consent.

BTHX 8120 - Dying in Contemporary Medical Culture

Credits:	2.0 [max 2.0]
Typically offered:	Every Fall

Examines practices of dying and death in contemporary U.S. culture, moral problems associated with these practices, possible solutions, and practical applications. Readings will consist of cultural critiques, bioethics literature, and empirical research.

CMB 5910 - Grantwriting: What Makes a Winning Proposal?

Credits:	2.0 [max 2.0]
Course Equivalencies:	CMB 5910/VMed 5910
Typically offered:	Every Spring

Components of a strong proposal. Grant submission process. What reviewers look for. How to locate grant announcements that match reserach interests.

CMB 5912 - Creativity

Credits:	1.0 [max 1.0]
Typically offered:	Every Spring

Creativity will be explored and used to provide new perspectives on a variety of professional goals, activities and challenges. Lectures will be followed by a mixture of individual and group activities to provide a guided exploration of how these creative approaches can be applied to many situations. Students will learn skills to expand their vision, become more adept at problem solving, design more innovative research, inspire themselves and others and become more fascinating communicators.

GCC 5022 - The Human Experience of Sensory Loss: Seeking Equitable and Effective Solutions (TS)

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Periodic Fall & Spring

This course focuses on the visual, auditory, and other sensory pathways that convey information about the world to mind and brain. Millions of people worldwide experience deficits in sensory function that affect their quality of life. We will focus on the characteristics of healthy sensory functioning as well as how sensory disorders can affect personal identity, impede information processing, and alter brain structure and function. The course will address the demographics and risk factors for sensory disabilities, the implications of these disabilities for activities of daily living, the history of society's response to sensory disability, as well as societal, ethical, and personal attitudes toward sensory disabilities. The course will also explore translational and applied approaches for addressing sensory disabilities. Each class session will be co-taught by a pair of instructors, representing multiple scientific and social perspectives. A major goal of the course is to view sensory function and impairment from multiple perspectives cognitive science, neuroscience, medicine, engineering, society, consumers, ethics and social justice. The course will combine lectures, discussions, and student-led presentations of research papers. The course will include hands-on demonstrations of assistive technology and panel discussions with people with visual and hearing disabilities. During the semester, each student (or pairs of students) will develop a mini research proposal to address a real-world issue related to sensory impairment. The proposal must be translational in nature, and must include consultation with consumers of the proposed project. The final class session will be devoted to poster presentations of the mini proposals. The proposal report must include consideration of potentially opposing viewpoints about the proposed research. This course addresses two of our University's grand challenges: Advancing Health Through Tailored Solutions, and Just and Equitable Communities. This is a Grand Challenge Curriculum course.

HUMF 5874 - Human Centered Design to Improve Complex Systems

Credits:	4.0 [max 4.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Class participants will work together using design thinking frameworks to discover, define, develop, and propose solutions to help solve complex system problems. The class will use cognitive design methods and research to guide in developing prototypes that foster improved experiences in information delivery, processes of systems, and technology. Teams, will tackle complex real-world problems. Projects may focus on a variety of areas ranging from retail to health care. Coursework will primarily focus on team-based projects. Participants will immerse themselves the following activities while working towards remediating their chosen problems. ? insights gathering/research methods ? cognitive design methods and principles ? identifying strengths/weaknesses in actual vs. proposed systems ? implementation (prototyping) considerations/strategies The course will be highly interactive with little lecture. It will strive to foster critical thinking and will offer an environment where creativity can thrive. Students are expected to come to class fully prepared to interact during class time with the readings and research consumed outside class. Material from course readings will focus on cognitive design, systems thinking principles and will be interwoven during the discussions and class activities. This course is designed for students from a variety of backgrounds and programs, including students from Human Factors, the Academic Health Center, Graphic Design, Product Design, Retail, Interior Design, Landscape Architecture, Architecture, Biomedical Engineering, Mechanical Engineering, Industrial Engineering, and the Carlson School. Human Factors students working toward a Plan C Master?s degree may use this course as one of the two courses required to be 50% project-based.

MDI 5010 - Product Innovation & Development Management

Credits:	2.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

Framework for conceptualization, design, development, commercialization process for medical products. Survey of key steps in innovation, from engineering/business perspective. Cross-functional development of concepts/processes. prereq: Grad MDI student. Non-MDI graduate students and non-degree graduate students may register for this course with permission of the MDI program.

MILI 6235 - Pharmaceutical Industry: Business and Policy

Credits:	2.0 [max 2.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

Business/policy issues specific to pharmaceutical industry. Interdisciplinary perspectives, active involvement by industry leaders.

MILI 6589 - Medical Technology Evaluation and Market Research

Credits:	2.0 [max 2.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

This course aims to provide knowledge of the skills, data, and methodology required to critically evaluate new medical technologies in order to meet financial investment as well as regulatory compliance objectives, such as FDA approval. The course is designed to provide an introduction to the analytic tool kit needed to critically evaluate new medical technology, such as cost-benefit analysis, cost effectiveness analysis as well as other decision-analytic models and markov-models.

MILI 6726 - Medical Device Industry: Business and Public Policy

Credits:	2.0 [max 2.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

This course, with the insight of industry leaders, addresses public-private sector interactions and the business, public policy, regulatory, and technology management issues that concern medical device and biotechnology companies.

MILI 6995 - Medical Industry Valuation Laboratory

Credits:	2.0 [max 6.0]
Grading Basis:	A-F only
Typically offered:	Every Fall, Spring & Summer

Interdisciplinary student teams create rapid production market analysis of promising medical technologies/services to determine potential for success in market. Exposure to University innovations, venture firms, inventors. prereq: Grad student

MOT 5001 - Technological Business Fundamentals

Credits:	2.0 [max 2.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall & Spring

Provides scientists and engineers with a working knowledge of the broader business context in which science and technology ideas are translated into solutions that address market needs and generate economic value. This two-unit course will broaden students? business knowledge and project leadership abilities, enabling technical professionals to increase their business impact and career success. The three modules of the course will build practical knowledge and skills in (1) project leadership, professionalism, teamwork, and effective communication, (2) the process of innovation (i.e., transforming technical ideas into value-creating solutions) and (3) business acumen fundamentals. prereq: Degree seeking or non-degree graduate students

MOT 5002 - Creating Technological Innovation

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

This hands-on, project-based course provides students the perspective of a Technology Leader of an organization or product team. Details the innovation process, from an idea's inception through impact in the economy, regardless of organizational setting. Explores how solutions are developed to become ready for broader market deployment. Includes testing and development of the problem-solution fit, probing of solutions for robustness, and testing of both technical and operational scaling of proposed solutions. Examines the human aspects of innovation, specifically issues of team building and readiness. Considers the broader system for innovation, including the role of key stakeholders in shaping its success in order to arrive at an impactful solution. Addresses intellectual property, the effect of regulations and social and cultural differences across varied global markets, and the personal skills necessary to align and manage these issues. prereq: Degree seeking or non-degree graduate students.

MOT 5003 - Technological Business Planning Workshop

Credits:	1.0 [max 2.0]
Grading Basis:	A-F only
Typically offered:	Every Fall & Spring

Applies lessons of 5001 or 5002 directly to technology of the student's choosing, possibly thesis topic. Aspects of strategic technology plan or business plan, culminating in presentation of plan. Must be taken in parallel with 5001 or 5002. prereq: Degree seeking or non-degree graduate students. Student must also enroll for MOT 5001 or MOT 5002.

MOT 5005 - Technically Speaking Leadership Lecture Series

Credits:	1.0 [max 1.0]
Grading Basis:	A-F only
Typically offered:	Every Fall & Spring

The course features a selection of highly accomplished industry speakers, including UMN alumni, who share their unique insights on industry developments, leadership, and innovation accumulated through experience in their careers. The lecture series serves as a discovery course for topics at the intersection of technology innovation and leadership. prereq: Degree seeking or non-degree graduate students

MOT 8502 - Innovation Leadership and Organizational Effectiveness

Credits:	1.0 [max 1.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

The MOT 8501 and 8502 sequence provides emerging and mid-career technology professionals with the leadership mindset, tool set, and skill set needed to focus, align, and engage multi-disciplinary individuals and teams in translating technology assets and foresight into customer solutions that generate profitable growth. MOT 8502 explores the role of outstanding leaders as developers of innovation strategy and architects of the organizational capability and team commitment needed to execute strategic choices. Emphasis is placed on principles and practices that help leaders focus on the right strategies, build the organizational capability required to execute a strategy, foster continuous improvement in individual and business performance, and lead change initiatives to sustain commitment versus compliance across diverse stakeholders. Students will practice improving their team effectiveness and develop a change leadership plan to support implementation of a key business initiative.

MPHY 5040 - Introduction to Medical Physics

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

Interactions and energy deposition by ionizing radiation in matter; medical imaging; radiation therapy physics and related radiation safety topics.

PDES 5701 - User-Centered Design Studio

Credits:	4.0 [max 4.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

This class provides a studio-based overview of user-centered product design and development processes. Students will practice both user and market research, creativity and idea generation tools, concept evaluation/selection techniques, prototyping methods for concept development and communication, and user testing. This class will also cover fundamentals of intellectual property and manufacturing. In this studio, students will apply these skills towards the development of a product concept.

PDES 5702 - Visual Communication

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

This class provides an overview of sketching, manual rendering and Adobe Photoshop, Illustrator, and InDesign for communication of conceptual product design. Topics covered will include free-hand perspective drawing of simple/complex geometries, line weight/quality, shading/shadow, design details and annotations, as well as image editing, vector graphics, and multi-page layout design. There will be weekly drawing assignments and critique of work.

PDES 5704 - Computer-Aided Design Methods

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

This class provides an overview of how to make high-quality digital computer-based models of existing and conceptual products and interactions. Students will learn Adobe Photoshop, Adobe Illustrator, and Axure for two-dimensional design and digital prototyping. Students will also learn SolidWorks and KeyShot for three-dimensional solid modeling and rendering. prereq: Senior or grad student

PHAR 5201 - Applied Medical Terminology

Credits:	2.0 [max 2.0]
Course Equivalencies:	Phar 1002/Phar 5201
Typically offered:	Every Fall, Spring & Summer

Interested in learning the difference between an antigen and an antibiotic? During this course, you will not only increase your medical vocabulary by more than 2500 words at your own pace, you will also learn to identify and articulately describe a wide variety of medical conditions and processes. Communication related to disease states, procedures, and diagnostics in health care can sometimes seem like another language. This course will help you recognize medical abbreviations, relate terms to procedures and diagnostics, and comprehend the meaning of medical terminology by using word elements. If you are interested in the health care field or would like to understand more about your own medical care, this course is a great place to start. Prereq: Basic knowledge of human anatomy/physiology

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

PUBH 6161 - Regulatory Toxicology

Credits:	2.0 [max 2.0]
Typically offered:	Every Spring

In-depth introduction to laws (and associated regulations) of U.S. federal regulatory agencies, such as CPSC, EPA, FDA, OSHA, and DOT, that require/use toxicological data/information in their mission of protecting human/environmental health. prereq: Background in toxicology or pharmacology or related field is recommended

PUBH 6414 - Biostatistical Literacy

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Every Fall, Spring & Summer

Develop ability to read/interpret statistical results in primary literature. Minimal calculation. No formal training in any statistical programming software. Biostatistical Literacy will cover the fundamental concepts of study design, descriptive statistics, hypothesis testing, confidence intervals, odds ratios, relative risks, adjusted models in multiple linear, logistic and Poisson regression, and survival analysis. The focus will be when to use a given method and how to interpret the results, not the actual computation or computer programming to obtain results from raw data. prereq: MPH or certificate student or environmental health or instr consent

PUBH 7415 - Introduction to Clinical Trials

Credits:	3.0 [max 3.0]
Course Equivalencies:	PubH 3415/PubH 7415
Typically offered:	Every Fall & Summer

Hypotheses/endpoints, choice of intervention/control, ethical considerations, blinding/randomization, data collection/monitoring, sample size, analysis, writing. Protocol development, group discussions. prereq: 6414 or 6450 or one semester graduate-level introductory biostatistics or statistics or instr consent

PUBH 7420 - Clinical Trials: Design, Implementation, and Analysis

Credits:	3.0 [max 3.0]
Typically offered:	Every Spring

Introduction to and methodology of randomized clinical trials. Design issues, sample size, operational details, interim monitoring, data analysis issues, overviews. prereq: 6451 or concurrent registration is required (or allowed) in 6451 or 7406 or instr consent

RSC 5106 - Introduction to Rehabilitation Science

Credits:	1.0 [max 1.0]
Typically offered:	Periodic Fall

This is one of a series of seminar courses that prepares students to think critically in reading and discussing the literature in rehabilitation science and to speak and write persuasively on scientific topics. This semester, the seminar will focus on the past, present, and future of rehabilitation science. This course will include lecture presentations from rehabilitation science faculty for the first 50 minutes of the weekly class time, as well as discussion/interaction sessions planned jointly by assigned students and faculty for the second 50 minute session each week.

SLHS 5606 - Introduction to Augmentative and Alternative Communication

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall & Spring

Description of the range of augmentative and alternative communication applications for persons with developmental and acquired disabilities. Topics include assessment, intervention strategies, progress monitoring, generalization, and maintenance; collateral behavior resulting from AAC applications.

SLHS 5802 - Hearing Aids I

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall

Survey of modern hearing aids including history of development, electroacoustic functions, clinic and laboratory measurement techniques, sound field acoustics, techniques for selection. prereq: [[3305, 4801] or [CDIS 3305, CDIS 4801], SLHS grad] or instr consent

SLHS 5804 - Cochlear Implants

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Spring Odd Year

Implantable auditory prostheses. History of device development, including cochlear implants and auditory brainstem implants. Signal processing. Techniques for selection, fitting, and rehabilitation. Behavioral/physiological changes across life span. prereq: [[4802, 5801, 5802] or [CDIS 4802, CDIS 5801, CDIS 5802], SLHS grad] or instr consent

SLHS 8802 - Hearing Aids II

Credits:	3.0 [max 3.0]
Typically offered:	Every Spring

Instrumentation and methods for fitting and evaluating personal hearing aids; ear impression techniques and materials; repair and modification of hearing aids. prereq: 5802 or Cdis 5802 or instr consent

BMEN 8777 - Thesis Credits: Master's

Credits:	1.0 -18.0 [max 50.0]
Grading Basis:	No Grade
Typically offered:	Every Fall, Spring & Summer

(No description) prereq: Max 18 cr per semester or summer; 10 cr total required [Plan A only]

BMEN 8820 - Plan B Project

Credits:	2.0 -3.0 [max 3.0]
Typically offered:	Every Fall, Spring & Summer

Project chosen by student and adviser to satisfy M.S. Plan B project requirement. Written report required. prereq: BMEn MS student

AEM 5451 - Optimal Estimation

Credits:	3.0 [max 3.0]
Course Equivalencies:	AEM 5451/EE 5251
Typically offered:	Fall Even Year

Basic probability theory. Batch/recursive least squares estimation. Filtering of linear/non-linear systems using Kalman and extended Kalman filters. Applications to sensor fusion, fault detection, and system identification. prereq: [[MATH 2243 or STAT 3021 or equiv], [4321 or EE 4231 or ME 5281 or equiv]] or instr consent

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 8201 - Fluid Mechanics I

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall

Mathematical and physical principles governing the motion of fluids. Kinematic, dynamic, and thermodynamic properties of fluids; stress and deformation; equations of motion; analysis of rotational and irrotational inviscid incompressible flow; two-dimensional and three-dimensional potential flow. prereq: 4201 or equiv, Math 2263 or equiv

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 8233 - Multi-phase Flows: Fundamentals, Measurement, and Modeling

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Spring Even Year

Introduction to fluid flows with multiple interacting phases, with emphasis on cases in which a dispersed phase is carried by a continuous one. Droplet dynamics, bubbly flows and bubble-induced fluctuations, particle-turbulence interaction. Fundamentals of measurement techniques and modeling approaches. Elements of rheology for complex and active fluids.

AEM 8511 - Advanced Topics in Continuum Mechanics

Credits:	3.0 [max 6.0]
Grading Basis:	A-F or Aud
Typically offered:	Periodic Fall & Spring

Constitutive equations; invariance and thermodynamic restrictions. Nonlinear elasticity theory; exact solutions, minimization, stability. Non-Newtonian fluids; viscometric flows, viscometric functions, normal stress. Other topics may include reactive and/or nonreactive mixtures, nonlinear plasticity, and deformable electromagnetic continua. prereq: 5501 or instr 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 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 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 8431 - Controlled Drug and Gene Delivery: Materials, Mechanisms, and Models

Credits:	4.0 [max 4.0]
Course Equivalencies:	BMEn 8431/PHM 8431
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Physical, chemical, physiological, mathematical principles underlying design of delivery systems for drugs. Small molecules, proteins, genes. Temporal controlled release. prereq: Differential equations course including partial differential equations or instr consent

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

CEGE 8401 - Fundamentals of Finite Element Method

Credits:	3.0 [max 3.0]
Prerequisites:	4411 or #
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Elements of calculus of variations; weak and strong formulations of linear continuum and structural problems. Isoparametric elements and numerical integration. Basic concepts of error analysis and convergence. Analysis of plates and shells. Introduction to mixed methods and time dependent problems. prereq: 4411 or instr consent

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 8201 - Applied Math

Credits:	3.0 [max 3.0]
Course Equivalencies:	ChEn 4701/ChEn 8201
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Integrated approach to solving linear mathematical problems. Linear algebraic equations. Linear ordinary and partial differential equations using theoretical/numerical analysis based on linear operator theory. prereq: Chemical engineering grad student or instr consent

CHEN 8402 - Statistical Thermodynamics and Kinetics

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Introduction to statistical mechanical description of equilibrium and non-equilibrium properties of matter. Emphasizes fluids, classical statistical mechanics. prereq: Chemical engineering grad student or instr 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

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 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

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 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 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 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 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 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

IE 5522 - Quality Engineering and Reliability

Credits:	4.0 [max 4.0]
Course Equivalencies:	IE 3522/IE 5522
Typically offered:	Periodic Fall & Spring

Quality engineering/management, economics of quality, statistical process control design of experiments, reliability, maintainability, availability. prereq: [4521 or equiv], [upper div or grad student or CNR]

IE 8564 - Optimization for Machine Learning

Credits:	4.0 [max 4.0]
Typically offered:	Every Fall

Machine learning has been widely used in many areas such as computer vision, search engines, speech recognition, robotics, recommender systems, bioinformatics, social networks, and finance. It has become an important tool in prediction and data analysis. This course provides a comprehensive overview of important optimization models for machine learning. It also systematically provides a theoretical and computational study on various optimization methods for solving these models and more general problems.

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 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 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 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 8202 - General Algebra

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Classical field theory through Galois theory, including solvable equations. Symmetric, Hermitian, orthogonal, and unitary form. Tensor and exterior algebras. Basic Wedderburn theory of rings; basic representation theory of groups. prereq: 8201 or instr consent

MATH 8253 - Algebraic Geometry

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Periodic Fall

Curves, surfaces, projective space, affine and projective varieties. Rational maps. Blowing-up points. Zariski topology. Irreducible varieties, divisors. prereq: 8202 or instr consent

MATH 8441 - Numerical Analysis and Scientific Computing

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall

Approximation of functions, numerical integration. Numerical methods for elliptic partial differential equations, including finite element methods, finite difference methods, and spectral methods. Grid generation. prereq: [4xxx analysis, 4xxx applied linear algebra] or instr consent

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 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 8341 - Conduction

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Advanced understanding/application of conduction/diffusion to heat/mass transfer problems. Solving ordinary/partial differential equations related to physics of diffusion. Special topics in numerical microscale heat transfer. prereq: Undergrad class in heat transfer or instr consent

ME 8342 - Convection

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Heat transfer in fluids flowing around bodies and in tubes/ducts. Forced/natural convection. Laminar/turbulent flow regimes. Turbulent transport and modeling. High-speed flows, viscous dissipation, variable property effects. Application to heat exchange devices. Convective mass transfer. prereq: Grad level course on fundamentals of fluid mechanics that has a substantial component on viscous flows or instr consent

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

ME 8345 - Computational Heat Transfer and Fluid Flow

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall & Spring

Finite volume method for solution of governing equations for heat transfer and fluid flow. Mathematical models of turbulence. Construction of general computer program. Practical applications. prereq: CSE grad student

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

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

PUBH 6450 - Biostatistics I

Credits:	4.0 [max 4.0]
Grading Basis:	A-F only
Typically offered:	Every Fall & Spring

This course will cover the fundamental concepts of exploratory data analysis and statistical inference for univariate and bivariate data, including: ? study design and sampling methods, ? descriptive and graphical summaries, ? random variables and their distributions, ? interval estimation, ? hypothesis testing, ? relevant nonparametric methods, ? simple regression/correlation, and ? introduction to multiple regression. There will be a focus on analyzing data using statistical programming software and on communicating the results in short reports. Health science examples from the research literature will be used throughout the course. prereq: [College-level algebra, health sciences grad student] or instr consent

PUBH 6451 - Biostatistics II

Credits:	4.0 [max 4.0]
Typically offered:	Every Fall & Spring

This course will cover more advanced aspects of statistical analysis methods with a focus on statistical modeling, including: ? two-way ANOVA, ? multiple linear regression, ? logistic regression, ? Poisson regression, ? log binomial and ordinal regression, ? survival analysis methods, including Kaplan-Meier analysis and proportional hazards (Cox) regression, ? power and sample size, and ? survey sampling and analysis. There will be a focus on analyzing data using statistical programming software and on communicating the results in short reports. Health science examples from the research literature will be used throughout the course. prereq: [PubH 6450 with grade of at least B, health sciences grad student] or instr consent

PUBH 7440 - Introduction to Bayesian Analysis

Credits:	3.0 [max 3.0]
Typically offered:	Every Spring

Introduction to Bayesian methods. Comparison with traditional frequentist methods. Emphasizes data analysis via modern computing methods: Gibbs sampler, WinBUGS software package. prereq: [[7401 or STAT 5101 or equiv], [public health MPH or biostatistics or statistics] grad student] or instr consent

PUBH 7475 - Statistical Learning and Data Mining

Credits:	3.0 [max 3.0]
Typically offered:	Periodic Spring

Various statistical techniques for extracting useful information (i.e., learning) from data. Linear discriminant analysis, tree-structured classifiers, feed-forward neural networks, support vector machines, other nonparametric methods, classifier ensembles, unsupervised learning. prereq: [[[6450, 6452] or equiv], programming backgroud in [FORTRAN or C/C++ or JAVA or Splus/R]] or instr consent; 2nd yr MS recommended

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 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.

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Biomedical Engineering M.S.