I am a Computer Science Ph.D. student at University of Illinois Urbana-Champaign (UIUC), advised by Prof. Han Zhao. Previously, I obtained my dual bachelor’s degree in Data Science from the University of Michigan (UM) and in Electrical and Computer Engineering from Shanghai Jiao Tong University (SJTU).

My research interest is centered around trustworthy machine learning. I currently work on i) Improving the multi-task capabilities of foundation models (e.g, multilingual LLMs, model merging). ii) Enhancing the efficiency of LLMs (e.g., semi-supervised learning, MoE). Previously, I have worked on multi-objective optimization, domain adaptation and multimodal learning.

News

• [Mar 2025] My Microsoft GenAI internship work on efficient MoE editing is out! Check out how we compress auxiliary experts to save inference costs while maitaining performance!
• [Jan 2025] Our work on mechanistic interpretability is accepted at NAACL 2025!
• [Dec 2024] Localize-and-Stitch is accepted by TMLR! Check out how better localization improves model merging!
• [Oct 2024] My Microsoft Turing internship work on Multilingual Scaling Laws is out! With this law, you can compute optimal sampling ratios of langauges to design your multilingual pretraining mixture for any model size!
• [Sept 2024] Semi-Supervised Reward Modeling (SSRM) is accepted at EMNLP 2024!
• [Aug 2024] Start internship at Microsoft GenAI!
• [May 2024] Start internship at Microsoft Turing!
• [May 2024] Our work on robust multi-task learning is accepted at ICML 2024!
• [May 2024] Our work on gradual domain adaptation is accepted at JMLR!
• [May 2023] Start internship at Amazon!