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 mathematical foundations of machine learning. 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 centers on reasoning about machine learning from mathematical first principles, with a particular focus on high-dimensional probability and geometric deep learning. Previously, I have worked on structure-preserving generative models, including diffusion on Riemannian manifolds, normalizing flows, and sampling acceleration for discrete processes.
Currently, I am working on convergence bounds for Sequential Monte Carlo. Recently, I also worked on Geometric Flow Matching and Martingale Optimal Transport.
I am also interested in differential geometry, natural language processing, and algorithmic alignment.
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.
Highlighted Mathematics Coursework
- *MATH 8803 RIE: Optimal Transport: Theory and Applications (Fall 2025)
- *MATH 6221: Probability Theory for Engineers (Fall 2025)
- *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 3236: Statistical Theory (Spring 2025)
- MATH 4782: Quantum Information & Computation (Fall 2024)
- 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 8803 HOS: High-Dimensional Statistical Signal Processing and Optimization (Fall 2025)
- *ECE 8803 GDL: Generative and Geometric Deep Learning (Fall 2025)
- *CS 8803 DTA: Dynamics to Algorithms: Optimization, Sampling, and Games (Fall 2025)
- *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