Alumni-PhD

Thesis: Nonlinear Matrix Concentration and its application

Thesis: Sparsity, Nonconvexity and Geometric Constraints on Statistical Inverse Problems

"A triptych in computation: Deep learning for molecular mass spectra, sum-of-squares optimization, and the structure of diffusion models"

Thesis: Structured Low-Complexity Matrix and Tensor Approximation with Applications

Current Position: Algorithm Developer at Hudson River Trading

Thesis: Data-Driven Methods for Inverse Problems: Blending Data Assimilation and Machine Learning

Thesis: Complexity and Numerical Stability in Matrix Computations and Nonconvex Optimization

Thesis: Algebraic and Differential Geometry in Modern Optimization

Thesis: Asymmetric Transport in Continuous Topological Insulators

Thesis: Applied Topology and Geometry of Neural Codes and Data

Current Position: Quantitative Researcher

Thesis: Atmospheric Extremes Through the Lens of Transition Path Theory

Current Position: Postdoctoral Associate, Department of Earth, Atmospheric and Planetary Sciences, MIT

Thesis: Graph Matérn Fields with Applications in Inverse Problems and Machine Learning

Current Position: Postdoctoral Research Associate, Program in Applied and Computational Mathematics, Princeton University

Thesis: Designing Deep Generative Models with Symbiotic Composition

Current Position: Applied Scientist, Amazon