Chandrasekaran, Venkat

Advisor — 7 thesises

• 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.))
• Candogan, Utkan Onur — Convex Relaxations for Graph and Inverse Eigenvalue Problems (2020, Dissertation (Ph.D.))
• Ziani, Juba — Efficiently Characterizing Games Consistent with Perturbed Equilibrium Observations (2017, Master's thesis)
• Soh, Yong Sheng — Fitting Convex Sets to Data: Algorithms and Applications (2019, Dissertation (Ph.D.))
• Taeb, Armeen — Latent-Variable Modeling: Algorithms, Inference, and 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.))