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M.S. in Machine Learning at Carnegie Mellon University
Research on efficient, reliable, and aligned foundation models.
I am a second-year M.S. in Machine Learning student (And incoming Ph.D. in ML) at Carnegie Mellon University advised by Prof. William W. Cohen. Before CMU, I completed my B.S. in Computer Science at the University of Rochester, where I was advised by Prof. Jiebo Luo.
My research focuses on efficient training and inference, model alignment, and evaluation for large language and vision-language models. I am currently a Student Researcher at Google Research advised by Dr. Si Si, and I also collaborate with Prof. Jiaxin Huang and Prof. Haohan Wang.
Updates from papers, collaborations, and current roles.
🎓🎓 I will start my PhD in CMU MLD in Fall 2026.
New preprints on GroupDPO efficiency.
🥳🥳 Self-Calibration accepted by ICLR 2026.
🥳🥳 Survey paper on Reliable and Responsible Foundation Models accepted by TMLR.
🥳🥳 CrossWordBench accepted by COLM 2025.
New preprints on semi-structured LLM auditing and speculative decoding.
Preprint
International Conference on Learning Representations (ICLR)
Preprint
Second Conference on Language Modeling (COLM)
International Conference on Learning Representations (ICLR)
Conference on Neural Information Processing Systems (NeurIPS)
Pittsburgh · Rochester · St. Louis · Mountain View
The fastest way to reach me is by email. You can also find publication updates on Google Scholar, code on GitHub, and professional details on LinkedIn or DBLP.
