About me

Hi! I am an incoming PhD student at University of Pennsylvania, advised by Surbhi Goel (CIS) and Enric Boix-Adsera (Wharton Statistics & Data Science). I received my Bachelor’s degree in Computer science & Mathematics from Hong Kong University of Science and Technology (HKUST) in 2025.

My research interests lie in theory and empirical science of deep learning and LLMs.

• Theory: I am interested in fundamental theories that reveal principles of learning and scaling.
• Empirical Science: I am enthusiastic about designing sandbox settings to understand language model (and interplay with theory). I am broadly interested in interpretability, understanding reasoning and alignment properties of LLMs.

Overall I am passionate about opening the black box of neural network and LLM through all possible ways.

Education

• PhD in Computer & Information Science, University of Pennsylvania (Incoming)
• BSc in Computer Science & Mathematics, Hong Kong University of Science and Technology, 2025 (GPA 4.099/4.3, Rank 1st, before grad-school app.)
• Exchange (Computer Science), EPFL, 2024 Spring

Review Experience

• Conference / Journal: NeurIPS 2025, ICML 2025, L4DC 2025, NeurIPS 2024, TMLR
• Workshop: ICML 2024 Workshop on Theoretical Foundations of Foundation Models (TF2M), ICLR 2024 Workshop on Bridging the Gap Between Practice and Theory in Deep Learning (BGPT)

Selected Awards

• Chern Class Achievement Scholarship (Outstanding) (Highest Award for math graduates)
• HKUST Epsilon Fund Award 24’ (For top math students at HKUST, <5 undergraduates each year)

Academic Activities

• Heidelberg Laureate Forum, Heidelberg, Germany, Sep 2024
• LeT-All Mentorship Workshop, Learning Theory Alliance, Online, June 2024
• International Conference on Learning Representations (ICLR), Vienna, May 2024
• Conference on Parismony and Learning (CPAL), Hong Kong, Jan 2024