SELECTED PUBLICATIONS

* indicates equal contribution. † indicates equal senior contribution (co-advising and co-corresponding authors).

• Xuan Zhang*, Limei Wang*, Jacob Helwig*, Youzhi Luo*, Cong Fu*, Yaochen Xie*, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, YuQing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stark, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alan Aspuru-Guzik, Erik Bekkers, Michael Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Lio, Rose Yu, Stephan Gunnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess Smidt, and Shuiwang Ji
  Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
  [Paper] [Website]


• Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, and Shuiwang Ji
  Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction
  The 40th International Conference on Machine Learning (ICML), 2023.
  


• Limei Wang*, Haoran Liu*, Yi Liu*†, Jerry Kurtin, and Shuiwang Ji†
  Learning Hierarchical Protein Representations via Complete 3D Graph Networks
  International Conference on Learning Representations (ICLR), 2023.
  


• Limei Wang*, Yi Liu*, Yuchao Lin, Haoran Liu, and Shuiwang Ji
  ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs
  The 36th Annual Conference on Neural Information Processing Systems (NeurIPS), 2022.
  


• Keqiang Yan, Yi Liu†, Yuchao Lin, and Shuiwang Ji†
  Periodic Graph Transformers for Crystal Material Property Prediction
  The 36th Annual Conference on Neural Information Processing Systems (NeurIPS), 2022.
  


• Shuiwang Ji*, Meng Liu*, Yi Liu*, Youzhi Luo*, Limei Wang*, Yaochen Xie*, Zhao Xu*, Haiyang Yu*
  Frontiers of Graph Neural Networks with DIG
  ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) Hands-on Tutorial, 2022.
  


• Yi Liu*, Limei Wang*, Meng Liu, Yuchao Lin, Xuan Zhang, Bora Oztekin, and Shuiwang Ji
  Spherical Message Passing for 3D Molecular Graphs
  International Conference on Learning Representations (ICLR), 2022.
  


• Yi Liu and Shuiwang Ji
  CleftNet: Augmented Deep Learning for Synaptic Cleft Detection from Brain Electron Microscopy
  IEEE Transactions on Medical Imaging (TMI), 2021.
  


• Hongyang Gao*, Yi Liu*, and Shuiwang Ji
  Topology-Aware Graph Pooling Networks
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
  


• Meng Liu*, Youzhi Luo*, Limei Wang*, Yaochen Xie*, Hao Yuan*, Shurui Gui*, Haiyang Yu*, Zhao Xu, Jingtun Zhang, Yi Liu, Keqiang Yan, Haoran Liu, Cong Fu, Bora Oztekin, Xuan Zhang, and Shuiwang Ji
  DIG: A Turnkey Library for Diving into Graph Deep Learning Research
  Journal of Machine Learning Research (JMLR), 2021.
  


• Yi Liu, Hao Yuan, Lei Cai, and Shuiwang Ji
  Deep Learning of High-Order Interactions for Protein Interface Prediction
  The 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2020.
  


• Yi Liu, Hao Yuan, Zhengyang Wang, and Shuiwang Ji
  Global Pixel Transformers for Virtual Staining of Microscopy Images
  IEEE Transactions on Medical Imaging (TMI), 2019.
  


• Yi Liu, Hao Yuan, and Shuiwang Ji
  Learning Local and Global Multi-Context Representations for Document Classification
  The 19th IEEE International Conference on Data Mining (ICDM), 2019.