About me
Hi! I am an incoming Computer Science PhD student at University of Pennsylvania, advised by Surbhi Goel, and Enric Boix from Wharton Statistics and Data Science. I am about to graduate from The Hong Kong University of Science and Technology (HKUST), with BSc in Computer Science & Mathematics.
My research interest lies in generalization theory, optimization theory, and mechanistic interpretability. <!– My research interests lie in the theory and empirical science of deep learning and LLMs.
- Theory: I am interested in elegant theories that uncover fundamental principles of deep learning, as well as theories that can guide practical applications, such as mup transfer.
- Empirical Science: I am enthusiastic about using sandbox setups to explore the mechanisms of language models (and possibly the interplay with theory), including reasoning, alignment and interpretability. –>
Recent News
- May 2025, Reading papers about anytime acceleration of gradient descent, and multi-index model papers. Do connect if you share similar interests!
Education
- PhD in Computer & Information Science, University of Pennsylvania (Incoming)
- BSc in Computer Science & Mathematics, Hong Kong University of Science and Technology, 2025
- Exchange (Computer Science), EPFL, 2024 Spring
- Visiting, University of Michigan, 2024 Summer
Review Experience
- Conference / Journal: NeurIPS 2025, ICML 2025, L4DC 2025, NeurIPS 2024, TMLR
Selected Awards
- HKUST Epsilon Fund Award 24’ (For top math students at HKUST, <5 undergraduates each year)
- Chern Class Entry & Talent Scholarship 22’, 23’, 24’ (For top math students at HKUST)
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