🖋 About Me
I am a second-year Computer Science PhD Student at University of California, Berkeley, Berkeley AI Research Lab (BAIR), advised by Aditi Krishnapriyan. I am also a visiting researcher at Meta Fundamental AI Research (FAIR), FAIR Chemistry Group, advised by Brandon Wood and Zachary Ulissi. I received my B.Sc. with distinction in Data Science from Duke Kunshan University and Duke University, where I was mentored by Dongmian Zou and Kai Zhang. I also worked as a research intern at Microsoft Research Asia, Shanghai AI/ML Group led by Dongsheng Li.
My research interest mainly falls on Geometric Deep Learning and AI for Science. Recently, I have been particularly interested in exploring how to scale up machine learning models to tackle complex challenges in scientific domains. More broadly, I am interested in combining ideas from mathematics with machine learning, and using machine learning to solve interdisciplinary problems.
🔥 News
- [Sep 2024] Our new EScAIP model is accepted by NeurIPS 2024! 🎉
- [Sep 2024] Joined as a visiting researcher at Meta FAIR!
- [Jan 2024] Our work "CNN Kernels Can Be the Best Shapelets" is accepted by ICLR 2024! 🎉
- [Aug 2023] Starting my PhD at UC Berkeley!
- [May 2023] Graduated from Duke Kunshan University with distinction! 🎓
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📝 Publications
💬 Talks
The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains
Virtual, SciML Symposium @ Georgia Tech 2024
Kunshan, China, Learning on Graphs Conference Local Meetups 2024Stable Hyperbolic Neural Networks for Graph Generation and Classification
Tokyo, Japan, ICIAM 2023 Mathematics of Geometric Deep Learning MinisymposiumData Continuity Matters: Improving Sequence Modeling with Lipschitz Regularizer
Kigali, Rwanda, ICLR 2023 Spotlight Presentation, Oral 6 Track 5: Applications & Deep Learning
🏆 Awards and Honors
- [2024.5] NERSC GenAI for Science CFP Award (2500 GPU hrs) - U.S. Department of Energy
- [2023.10] Open Catalyst Challenge 3rd Place - NeurIPS 2023 Competitions
- [2023.5] Graduation with Distinction (Top 5%) - Duke Kunshan University
- [2023.5] Graduation with Latin Honors cum laude - Duke Kunshan University
- [2023.5] Zu Chongzhi Math Signature Work Award - Duke Kunshan Zu Chongzhi Math Center
- [2023.5] Conference Travel Grant (ICLR 2023) - Duke Kunshan University
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📖 Educations
2023.8 - present PhD Student in Computer Science, University of California, Berkeley
2019.8 - 2023.5 Dual Degree Undergraduate in Data Science, Duke Kunshan University / Duke University
🏢 Work Experiences
2024.9 - Present Meta Research, Fundamental AI Research
2022.5 - 2022.9 Microsoft Research, Shanghai AI/ML Group
2023.1 - 2023.6 Microsoft Research, Shanghai AI/ML Group
🏫 Services
Reviewer/PC Member: NeurIPS {2023, 2024}, ICLR {2024, 2025}, ICML 2024, AAAI 2025, AISTATS 2025, ACML 2024
Journal Reviewer: TNNLS
✈️ Travel Plans
2024.11 LoG Conference, Duke Kunshan University, Kunshan, China
2024.12 NeurIPS 2024, Vancouver, Canada