Tropp, Joel A.

Committee Member — 35 thesises

• McCoy, Michael Brian — A Geometric Analysis of Convex Demixing (2013, Dissertation (Ph.D.))
• Levin, Eitan — Any-Dimensional Data Science: Learning, Optimization, and Sampling (2026, Dissertation (Ph.D.))
• Murray, Riley John — Applications of Convex Analysis to Signomial and Polynomial Nonnegativity Problems (2021, Dissertation (Ph.D.))
• Sweatlock, Sarah Lynne — Asymptotic Weight Analysis of Low-Density Parity Check (LDPC) Code Ensembles (2008, Dissertation (Ph.D.))
• Khajehnejad, M. Amin — Combinatorial Regression and Improved Basis Pursuit for Sparse Estimation (2012, Dissertation (Ph.D.))
• Faulkner, Matthew Nicholas — Community Sense and Response Systems (2014, Dissertation (Ph.D.))
• Yoo, Juhwan — Compressed Sensing Receivers: Theory, Design, and Performance Limits (2012, Dissertation (Ph.D.))
• Plan, Yaniv — Compressed Sensing, Sparse Approximation, and Low-Rank Matrix Estimation (2011, Dissertation (Ph.D.))
• Xu, Weiyu — Compressive Sensing for Sparse Approximations: Constructions, Algorithms, and Analysis (2010, Dissertation (Ph.D.))
• Horstmeyer, Roarke William — Computational Microscopy: Turning Megapixels into Gigapixels (2016, Dissertation (Ph.D.))
• Chen, Yuhua Richard — Concentration Inequalities of Random Matrices and Solving Ptychography with a Convex Relaxation (2017, Dissertation (Ph.D.))
• Stobbe, Peter — Convex Analysis for Minimizing and Learning Submodular Set Functions (2013, Dissertation (Ph.D.))
• Jaganathan, Kishore — Convex Programming-Based Phase Retrieval: Theory and Applications (2016, Dissertation (Ph.D.))
• Oymak, Samet — Convex Relaxation for Low-Dimensional Representation: Phase Transitions and Limitations (2015, Dissertation (Ph.D.))
• Slote, Joseph Alfred — Discrete Harmonic Analysis and its Applications to Testing, Learning, and Complexity (2025, Dissertation (Ph.D.))
• Soh, Yong Sheng — Fitting Convex Sets to Data: Algorithms and Applications (2019, Dissertation (Ph.D.))
• Schäfer, Florian Tobias — Inference, Computation, and Games (2021, Dissertation (Ph.D.))
• Shankar, Krishna — Kinematics and Local Motion Planning for Quasi-static Whole-body Mobile Manipulation (2016, Dissertation (Ph.D.))
• Huang, Hsin-Yuan (Robert) — Learning in the Quantum Universe (2024, Dissertation (Ph.D.))
• Zhang, Ziyun — Low-Rank Matrix Recovery: Manifold Geometry and Global Convergence (2023, Dissertation (Ph.D.))
• Epperly, Ethan Nicholas — Make the Most of What You Have: Resource-Efficient Randomized Algorithms for Matrix Computations (2025, Dissertation (Ph.D.))
• Vyetrenko, Svitlana S. — Network Coding for Error Correction (2011, Dissertation (Ph.D.))
• Bernstein, Jeremy David — Optimisation & Generalisation in Networks of Neurons (2023, Dissertation (Ph.D.))
• Batlle Franch, Pau — Optimization-Based Statistical Inference: Constrained Inverse Problems, Worst-Case Priors, and Kernel Regression (2025, Dissertation (Ph.D.))
• Becker, Stephen R. — Practical Compressed Sensing: Modern Data Acquisition and Signal Processing (2011, Dissertation (Ph.D.))
• Chen, Chi-Fang — Quantum Gibbs Sampling (2025, Dissertation (Ph.D.))
• Vakili, Ali — Random Matrix Recursions in Estimation, Control, and Adaptive Filtering (2011, Dissertation (Ph.D.))
• Ahn, Hyoung Jun — Random Propagation in Complex Systems: Nonlinear Matrix Recursions and Epidemic Spread (2014, Dissertation (Ph.D.))
• Bruer, John Jacob — Recovering Structured Low-rank Operators Using Nuclear Norms (2017, Dissertation (Ph.D.))
• Thrampoulidis, Christos — Recovering Structured Signals in High Dimensions via Non-Smooth Convex Optimization: Precise Performance Analysis (2016, Dissertation (Ph.D.))
• Douik, Ahmed — Riemannian Optimization for Convex and Non-Convex Signal Processing and Machine Learning Applications (2020, Dissertation (Ph.D.))
• Moreno Ferreira, Elvira — Scalable Approximation through Structure: Spectral Methods for Polynomial Optimization and Adaptive Sampling in Kernel Quadrature (2026, Dissertation (Ph.D.))
• Gittens, Alex A. — Topics in Randomized Numerical Linear Algebra (2013, Dissertation (Ph.D.))
• Gao, Angela Fang — Uncovering Hidden Structure in Data and the Physical World for Seismic Tomography and Beyond (2026, Dissertation (Ph.D.))
• Abbasi, Ehsan — Universality Laws and Performance Analysis of the Generalized Linear Models (2020, Dissertation (Ph.D.))