The MCAM program consists of at least nine graduate level courses related to Computational and Applied Mathematics, as described below, and can be completed in as few as nine months or up to two years.
Working with your academic advisers, you will develop a course program and select one of the following tracks. Each track includes a sequence of three courses.
| Computational Mathematics Track | Applied Analysis and Modeling Track |
|---|---|
You will complete three additional courses of your choice, selecting from the track you did not pursue above or from other courses offered as part of the CAM graduate programs. Some courses may have prerequisite requirements or require instructor consent in order to enroll. Recent course offerings have included (but are not limited to) the list below.
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For the remaining courses, you can select from the above lists or from graduate-level courses related to CAM offered through the Physical Science Division, TTIC, or the Booth Business School.
Thesis Option
Students interested in pursuing applications to a PhD program are encouraged to take the option of a MS degree with thesis.
To pursue this option, you will be required to:
- Complete the requirements above
- Write and defend a master’s thesis under the guidance of a CAM faculty advisor.
The program does not have a separate period of study allocated to thesis work, so students continue to take courses while working on their thesis.
For more information, please view the 2025-2026 Handbook.
Wentao Yang - Advisor: Anitescu
Thesis Title: Online Planning Monte-Carlo Algorithm with UCT for Partially Observable Markov Decision Processes Problems
Yue Tu - Advisor: Liang/Khoo
Thesis Title: Quantum Advantage in Learning Mixed Unitary Channel
Rongze Wei - Advisor: Anitescu
Thesis Title: Numerical and Analytical Study of Action Minimization for Rare Event Estimation
Mike Wang - Advisor: Silber
Thesis Title: Causation Entropy-Guided Discovery of Governing Partial Differential Equations
Rizheng Huang - Advisor: Khoo
Thesis Title: Solving Quantum Two-marginal Relaxation with Sparse plus Low Rank Matrix
Jifeng Luo - Advisor: Khoo
Thesis Title: Efficient Imaginary-Time Evolution using Coupled-Cluster Reparameterization
Yihan Guo - Advisor: Lim
Thesis Title: Eigen, singular, cosine-sine, and Autonne–Takagi vectors distributions of random matrix ensembles
Nicolas Schmid - Advisor: Kondor
Thesis Title: SE(3)-Equivariant Convolutional Neural Networks with Interpolation-Based Kernels Applied to Biomedical Imaging
Yuelong Li - Advisor: Bal
Thesis Title: Topological Stability and Novel Edge Quantization in Non-Uniform Rhombohedral Graphene
Russell Hua - Advisor: Bal
Thesis Title: Existence of Scattering Solutions to Weakly Nonlinear Schrodinger Equations
Lekun Wang - Advisor: Barber
Thesis Title: Distribution-Free Uncertainty Quantifications with Conditional Guarantees for Image-To-Image Regression Models
Ruizhe Chen - Advisor: Xiu
Thesis Title: Forecasting Macroeconomic Variables Using Principle Component Analysis and Supervised Sparse Autoencoders
Matthew Frazier - Advisor: Bal
Thesis Title: Topological Properties of Cold Plasma
Yuelian Li - Advisor: Kondor
Thesis Title: Implementing and Evaluating a P-Tensor-based Framework on Node and Graph Classification Tasks
Jingchun Shao - Advisor: Khoo
Thesis Title: Quantized Tensor Train for Compressed Sensing
Alex Huang - Advisor: Ma
Thesis Title: Scaled Gradient Descent for Low-Rank Adaptation in Language Model Fine-Tuning
Kaiwen Fu - Advisor: Sanz-Alonso
Thesis Title: Through Variational Inference to Data Assimilation
Haoming Wang - Advisor: Lim
Thesis Title: Glivenko-Cantelli for f-divergence