Recipient of the Google Ph.D. Fellowship. Published multiple papers including 'Scalable and Robust LLM Unlearning by Correcting Responses with Retrieved Exclusions', 'Think Clearly: Improving Reasoning via Redundant Token Pruning', and more.
Research Experience
During his Ph.D., he interned or closely collaborated with Xian Li at Meta FAIR, Jonathan Richard Schwarz at Google DeepMind (now at Thomson Reuters), Yee Whye Teh at the University of Oxford, and Jaeho Lee at POSTECH.
Education
Obtained his Ph.D. degree at KAIST, where he was advised by Jinwoo Shin.
Background
A Senior Researcher at the AI Interaction and Learning group in Microsoft Research Redmond. His research primarily focuses on developing efficient machine learning frameworks to address scalability challenges posed by large-scale models, particularly large language models.