Hi! I'm a third-year undergraduate at the Georgia Institute of Technology studying Mathematics. I am fortunate to work with Prof. Yongxin Chen and Prof. Amirali Aghazadeh on the mathematics of machine learning, with a focus on generative models. Outside of research, I enjoy photography, writing, reading, and bouldering. This past summer I participated in a REU at Williams College; next summer I'll be a Quantitative Trading Intern at Susquehanna International Group (SIG).
Research
My research focuses on understanding machine learning from mathematical first principles. I have worked on the theoretical foundations for diffusion models on Riemannian manifolds, convexity-preserving normalizing flows using optimal transport, and sampling acceleration for discrete processes, particularly for structured biological data. My current work involves generalizing Wasserstein gradient flows to equilibrium matching for molecular dynamics, establishing nonasymptotic convergence bounds for sequential Monte Carlo samplers on non-log-concave distributions, and developing statistical methods for estimating martingale optimal transport plans.
I am also interested in differential geometry, natural language processing, and high-dimensional statistics.
Academics
I have taken a fair amount of undergraduate and graduate courses in mathematics and computer science. Here are some highlights, with * indicating graduate courses.
In Progress (Fall 2025)
- *MATH 8803 RIE: Optimal Transport: Theory and Applications
- *ECE 8803 HOS: High-Dimensional Statistical Signal Processing and Optimization
- *ECE 8803 GDL: Generative and Geometric Deep Learning
- *CS 8803 DTA: Dynamics to Algorithms: Optimization, Sampling, and Games
- *MATH 6221: Probability Theory for Engineers
Highlighted Mathematics Coursework
- *MATH 7339: Advanced Analysis (Spring 2025)
- *MATH 6455: Differential Geometry I (Spring 2025)
- *MATH 6579: Measure Theory for Engineers (Fall 2024)
- *MATH 6121: Algebra I (Fall 2024)
- *MATH 8803 GHO: Geometric Inequalities (Fall 2024)
- MATH 4782: Quantum Information & Computation (Fall 2024)
- MATH 3236: Statistical Theory (Spring 2025)
- MATH 4441: Differential Geometry (Fall 2024)
- MATH 4150: Intro To Number Theory (Spring 2024)
- MATH 3235: Probability Theory (Spring 2024)
- MATH 4022: Intro to Graph Theory (Fall 2023)
- MATH 3406: Second Course in Linear Algebra (Fall 2023) notes
Highlighted Computer Science & ECE Coursework
- *ECE 7751: Graphical Models in Machine Learning (Spring 2025)
- *ECE 6270: Convex Optimization (Spring 2025)
- *ECE 6254: Statistical Machine Learning (Spring 2025)
- CS 4650: Natural Language Processing (Fall 2024)
- CS 3511: Design and Analysis of Algorithms - Honors (Spring 2024)
Contact
ec [at] gatech [dot] edu / linkedin