🧑💻 Biography
I am now a third-year Ph.D. student of the Institute for Artificial Intelligence of Peking University, advised by Prof. Muhan Zhang. Our group’s github page is GraphPKU.
My recent research focuses on generative models that span multiple modalities, including molecules, images, and videos. Previously, I have worked on geometric deep learning, particularly investigating the theoretical expressiveness of geometric models and developing powerful models within this domain. If you are interested in these areas, feel free to reach out!
🎖 Honors and Awards
- 2025.10, Doctoral Dean’s Scholarship, Institute for Artificial Intelligence, Peking University
- 2020.12, 2021.12, 2022.12, National Scholarship for Undergraduate Student
- 2021.12, Outstanding Student Pioneer of Tianjin University (Nomination Award) (only 10 awardees and 5 nominated awardees university-wide per year)
- 2021.08, First Prize of National Zhou Peiyuan Competition on Mechanics (~0.3%)
- 2021.04, Meritorious Winner (First Prize) of ICM: Interdisciplinary Contest In Modeling
📖 Educations
2023.09 -, Ph.D. student, Institute for Artificial Intelligence, Peking University
2019.09 - 2023.07, B.E., School of Future Technology, Tianjin University
💻 Internships
- 2021.08 - 2022.04, Fib-Lab, Tsinghua University
📃 Publications
- Zian Li, Muhan Zhang, CanvasMAR: Improving Masked Autoregressive Video Generation With Canvas, arxiv-preprint.
- Zian Li, Cai Zhou, Xiyuan Wang, Xingang Peng, Muhan Zhang, Geometric Representation Condition Improves Equivariant Molecule Generation, International Conference on Machine Learning (ICML-25), 2025, Spotlight.
- Zian Li, Xiyuan Wang, Shijia Kang, Muhan Zhang, On the Completeness of Invariant Geometric Deep Learning Models, International Conference on Learning Representations (ICLR-25), 2025. (Source code)
- Zian Li, Xiyuan Wang, Yinan Huang, Muhan Zhang, Is Distance Matrix Enough for Geometric Deep Learning?, Advances in Neural Information Processing Systems (NIPS-23), 2023. (Source code)