Publications

• A Multi-Grained Symmetric Differential Equation Model for Learning Protein-Ligand Binding Dynamics.
  Liu, S., Du, W., Li, Y., Li, Z., Bhethanabotla, V., Rampal, N., Yaghi, O., Borgs, C.,Anandkumar, A., Guo, H., & Chayes, J.
  [In Submission to Nature Communication] [Project Page]
• Manifold-Constrained Nucleus-Level Denoising Diffusion Model for Structure-Based Drug Design.
  Liu, S., Yan, D., Du, W., Liu, W., Li, Z., Guo, H., Borgs, C., Chayes, J., & Anandkumar, A.
  [In Submission to Proceedings of the National Academy of Sciences of the United States of America (PNAS)] [Project Page]
• Identification of Cu-N2 Sites for Zn-Air Batteries in Harsh Electrolytes: Computer Virtual Screening, Machine Learning, and Practical Application.
  Xu, C., Li, K., Liu, S., Xu, J., Sharma, S., Zhang, J., Mao, B., Chen, H., Zhang, H., Xu, H., Luo, B., Zhao, H., Li, Z., Huang, Z., Wang, J., Xi, K., Fu, C., Zhao, Y., Chai, G., He, G., & Parkin, I. [.
  [In Submission to Energy and Environmental Science] [Project Page]
• A Text-guided Protein Design Framework.
  Liu, S., Li, Y., Li, Z., Gitter, A., Zhu, Y., Lu, J., Xu, Z., Nie, W., Ramanathan, A., Xiao, C., Tang, J., & Anandkumar, A.
  [In Submission to Nature Machine Intelligence (Second-round Revision)] [Project Page]
• Unsupervised Discovery of Steerable Factors When Graph Deep Generative Models Are Entangled.
  Liu, S., Wang, C., Lu, J., Nie, W., Wang, H., Li, Z., Zhou, B., & Tang, J.
  [Transactions on Machine Learning Research 2024] [Project Page]
• Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials.
  Liu, S., Du, W., Li, Y., Li, Z., Zheng, Z., Duan, C., Ma, Z., Yaghi, O., Anandkumar, A., Borgs, C., Chayes, J., Guo, H., & Tang, J..
  [NeurIPS Dataset and Benchmark 2023] [Project Page]
• [Other Figure Visualization Works]