Yuchao Lin
- Postdoctoral Researcher, Caltech
I am a postdoctoral researcher at Caltech working with Prof. Anima Anandkumar at the Anima AI + Science Lab. Previously, I completed my Ph.D. at Texas A&M University supervised by Prof. Shuiwang Ji at DIVE lab. Before that, I was a research assistant at Nanjing University advised by Prof. Yang Yu. My research interest is in the broad application of invariant and equivariant geometric graph learning for 3D atomic systems.
Research Interests:
Artificial Intelligence for Science | Symmetry Learning | Geometric Graph Neural Networks
Research Interests:
Artificial Intelligence for Science | Symmetry Learning | Geometric Graph Neural Networks
Selected Publications
- Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, ..., Tess Smidt, Shuiwang Ji. (Foundations and Trends in Machine Learning). [pdf] [code]
- Spin-Weighted Spherical Harmonics Enable Complete and Scalable E(3)-Equivariant Networks. Chenxing Liang*, Yuchao Lin*, Andrii Kryvenko*, Wendi Yu, Chuan Li, Jianwen Xie, Xiaofeng Qian, Shuiwang Ji. (NeurIPS 2026). [pdf] [code]
- Tensor Decomposition Networks for Fast Machine Learning Interatomic Potential Computations. Yuchao Lin*, Cong Fu*, Zachary Krueger, Haiyang Yu, Maho Nakata, Jianwen Xie, Emine Kucukbenli, Xiaofeng Qian, Shuiwang Ji. The 39th Annual Conference on Neural Information Processing Systems, (NeurIPS 2025). [pdf] [code]
- Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency. Yuchao Lin, Jacob Helwig, Shurui Gui, and Shuiwang Ji. Proceedings of the 41st International Conference on Machine Learning, (ICML 2024 Spotlight [3.5% Acceptance Rate]). [pdf] [code]
- JARVIS-Leaderboard: A Large Scale Benchmark of Materials Design Methods. Kamal Choudhary, Daniel Wines, Kangming Li, ..., Keqiang Yan, Yuchao Lin, Shuiwang Ji, ..., Adam J. Biacchi, Francesca Tavazza. (npj Computational Materials 10, 93 (2024)). [pdf]
- Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction. Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, and Shuiwang Ji. Proceedings of the 40th International Conference on Machine Learning, (ICML 2023). [pdf] [code] [math overview]