Computational Bioengineering Graduate Track
Computation plays an ever larger role in Bioengineering (as it does in most scientific disciplines) and this track seeks to provide students with specialized training in scientific computing. Specific areas of computation relevant to the Bioengineering program include geometric modeling, simulation, computational biomechanics, statistical signal processing, control and optimization, medical imaging, and scientific visualization. Research topics that make use of these approaches within the Department include simulation of cardiac and neural physiology, analysis of signals in electrophysiology, musculoskeletal biomechanics, medical imaging, and mathematical biology.
Masters Students
M.S. students in the Computational Bioengineering Track must successfully
complete the course requirements outlined below, as well as the total
course credit hour requirement of the M.S. degree program.
- Any one from the following courses that cover a broad spectrum of numerical and computational methods:
- CS 5210/6210: Advanced Scientific Computing I (3)
- CS 6220: Advanced Scientific Computing II (3)
- MATH 5610: Introduction to Numerical Analysis I (4)
- Math 5620: Introduction to Numerical Analysis II (4)
- Math 5600: Survey of Numerical Analysis (4)
- A second, advanced course in numerical and computational techniques
from the electives list below. The student will select this course
in consultation with the advisory committee so that it provides
specialized material in topics relevant to the anticipated thesis
research project.
- One course in biomedical computing taught by the Bioengineering
Department, for example, BE 6900 (Quantitative Neuroscience),
BE 7420 (Modeling of Physiological Systems), a special topics
class, or a directed reading course.
Ph.D. Students
Ph.D. students in the Computational Bioengineering Track are expected to have general knowledge in computational and numerical methods as well as in one field of bioengineering application. A student who, for example, applied computational methods to problems in cardiac electrophysiology, should have knowledge in both areas. The material for the exam will be based on topics covered in a variety of courses, however, there will be a strong emphasis on the integration of computational approaches and the target area of application, material not likely to be covered explicitly in any course or text book.
As with other tracks, approximately 25% of the material in the qualifying exam will come from material in the Bioengineering core curriculum covered in the comprehensive exam. The remainder will come from topics in both computational methods and the topic area selected by the student for his or her PhD research. Some relevant examples of the latter topic areas include cardiac electrophysiology, neurophysiology, biomechanics, and medical imaging.
Courses that will be of special importance in the computational component of the qualifying exam are those listed for the M.S. program above
Computational Bioengineering Course Program of Study
The course selection that will be appropriate for each student in the 8computational Bioengineering track may vary quite a bit more than for other tracks. The goal of the course selection should be to provide the required and appropriate computation and mathematical background but also the special knowledge of the system under study. The Program of Study is a list created by the student and the supervisory committee of all courses to be completed by the student as part of the requirements for the Ph.D. The Program of Study requires formal approval by the student's advisor, Dissertation Supervisory Committee, and Director of Graduate Studies.
Additional Computational Bioengineering Courses
Bioengineering
- BIOEN 6900 Quantitative Neuroscience
- BIOEN 7210 Biosolid Mechanics
- BIOEN 7220 Biofluid Mechanics
- BIOEN 7420 Modeling of Physiological Systems
Computer Science (scientific computing and software)
- CS 5020: Algorithms and Data Structures
- CS 5010: Software Practice
- CS 5630/6630: Scientific Visualization (3)
- CS 5954/6964: Introduction to Digital Image Processing
- CS 5963/6963: Computational Geometry
- CS 6820: Parallel Computer Architecture
- CS 7120: Information Based Complexity
- CS 7240: Sinc Methods
- CS 5600/6600, 5610/6610: Computer Graphics
- CS 6670, 6680: Computer-Aided Geometric Design
- CS 6939: Seminar in Inverse Problems (1-3).
Electrical Engineering (signal processing, electromagnetics)
- EE3500 Fundamentals of Signals and Systems
- EE5510 Random Processes
- EE5540 Digital Signal Processing
- EE5551 Survey of Optimization Techniques
- EE6510 Statistical Communication Theory
- EE6540 Estimation Theory
- EE6550 Adaptive Filters
- EE6560 Multivariable Systems
- EE6640/1 Advanced Digital Signal Processing I/II
- EE6340 Numerical Techniques in Electromagnetics
Mathematics (numerical methods)
- Math 5110 Mathematical Biology I (3)
- Math 5120 Mathematical Biology II (3)
- Math 5040 Stochastic Processes and Simulation I (3)
- Math 5050 Stochastic Processes and Simulation II (3)
- Math 5250 Matrix Analysis (3)
- Math 5440 Introduction to Partial Differential Equations (3)
- Math 5470 Applied Dynamical Systems (3)
- MATH 5740 Mathematical Modeling (2)
- Math 6630 Numerical Solutions of Partial Differential Equations (3)
- Math 6740 Bifurcation Theory (3)
- Math 6750 Continuum Mechanics: Fluids (3)
- Math 6760 Continuum Mechanics: Solids (3)
Mechanical Engineering
- MEEN 6005 Exploration of Complex Continuum Phenomena I
- MEEN 6015 Exploration of Complex Continuum Phenomena II
- MEEN 5510/6510 Introduction to Finite Elements
- MEEN 5720 Computational Fluid Dynamics
- MEEN 6200 Advanced Modeling and Control
- MEEN 7010 Computer-aided Engineering
- MEEN 7540 Advanced Finite Elements
- MEEN 7200 Nonlinear Controls
Medical Imaging
- Radiology 7310: Advanced Topics in Magnetic Resonance Imaging (Dr. Parker, 3 credit hours, cross-listed as BIOEN 7310 and ELEN 7310)
- RDLGY 7320: 3D Reconstruction Techniques in Medical Imaging (Dr. Clackdoyle , 3 credit hours, cross-listed as BIOEN 7320 and ELEN 7320)
Psychology
- Introduction to Computational Neuroscience
Questions?
Questions regarding the Computational Bioengineering track should be directed to Dr. Rick Rabbitt (801 581-6968), Dr. Rob Macleod, or Jeff Weiss