My research interests lie at the intersection of Machine Learning Systems, Optimization Theory, High Performance Computing, and AI for Science, where I leverage my mathematical and engineering talents to pioneer cutting-edge solutions. I work at Cornell Relax ML Lab advised by Prof. Chris De Sa on efficient machine learning algorithms and systems. Grounded in mathematical principles, our work aims to expedite large-scale, high-performance machine learning systems that are efficient, parallel, and distributed in real-world settings. Parallel to this, I collaborate on AI-driven molecule generation with talented Ph.D. students.

My academic journey has led me to a Master of Engineering in Computer Science at Cornell University. Prior to this, I pursued dual B.S. degrees in Computer Science and Mathematics at the University of Massachusetts Amherst, complemented by a minor in Japanese. My specialization in Mathematics focused on Applied Math and Scientific Computing. Prior to my graduation, I engaged in research at the UMass BioNLP Lab under Prof. Hong Yu, concentrating on bio-medical and clinical NLP applications within Electronic Health Records.

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