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I am a Ph.D. Candidate in the Department of Computer Science at the University of Southern California, advised by Prof. Xuezhe Ma. I received my Master of Science in Computer Science from New York University, where I was advised by Prof. Yi-Jen Chiang, Prof. Christopher Musco, and Prof. Yi Fang. Before that, I was an undergraduate student in EECS at the University of Michigan, Ann Arbor.
My research focuses on improving the efficiency of large language model (LLM) pre-training. I work on methods that scale from small proxy models to large foundation models, as well as the mathematical principles underlying training dynamics. I work on hyperparameter optimization, especially transferring hyperparameter configurations from small models to large-scale models. In particular, I study scaling-aware parameterizations such as maximum update parametrization (μP). I also study optimizers for large-scale training. Previously, I worked on transfer learning with theoretical guarantees, adversarial machine learning for 3D point cloud models, and streaming algorithms for time-varying volume data.
(* indicates equal contribution.)
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