I'm a computer science student at Carnegie Mellon University pursuing a senior thesis on multi-task constraint learning.
My research interests lie at the intersection of imitation learning and game theory. I'm also broadly interested in topics adjacent to rendering, physical simulation, and designing and optimizing low-level systems.
Notable projects:
parallel fluid simulation in CUDA
efficient fine-tuning of large-scale pretrained models
unsupervised, interpretable image editing
Previously, I've worked at Jump Trading, Meta AI, and Meta. At Carnegie Mellon, I've been a teaching assistant for 15-251, an introductory course on theoretical computer science.
In my free time, I enjoy playing chess, poker, and going bouldering.