The Course Inventory below includes only those courses administered by the CSEM program. Our students take many courses administered by other UT departments, some of which are also cross-listed with CSEM. Refer to our Approved Course List for a comprehensive list of courses that fulfill CSEM program requirements.
Note: All course selections must be approved by the Graduate Advisor. See Graduate Catalog for full course descriptions.
Area A – Applicable Mathematics. Area A encompasses the mathematical theory and foundations underlying the scientific models and computational science addressed in the overall research effort. It may involve, for example, functional analysis, partial differential equations, differential geometry, probability, data science, optimization, and approximation theory.
Area B – Numerical Analysis and Scientific Computation. Area B, encompasses all areas of algorithms and computational simulation, as well as their development, verification, and analysis. It often covers, for example, issues of numerical stability and approximation, scientific programming, visualization, parallel computation, software design, and high performance computing.
Area C – Mathematical Modeling and Applications. Area C encompasses the scientific principles of the natural, engineered, social, or other system that motivates the research and aims to foster some scientific or societal goal through computational modeling and simulation. With the assistance of a CSEM faculty member, all students are expected to develop a concentration of course work in a well-defined discipline of science, engineering, medicine, economics, or the social sciences. The number of courses, and their depth and sophistication, in general, depend on the background and interest of the individual student.
The Chair of the Graduate Studies Committee approves courses for Areas A, B, and C when it is clear to what area they belong. For courses where the determination is unclear, the CSEM Graduate Studies Subcommittee provides an evaluation and determination.
A course may be considered as Area C if the following criteria are met:
In general, Math (M), Computer Science (CS), and Statistics and Data Science (SDS) courses are not to be considered as Area C. However, a student can petition for a specific course to be counted. The PhD advisor will need to give a brief statement as to why alternative courses are not suitable and discuss how the proposed course fits the criteria above for an Area C course.