Kaiyuan Gao (高开元 in Chinese) is currently a member of the joint Ph.D. program between Huazhong University of Science and Technology (HUST) and Microsoft Research AI4Science (Asia), advised by Prof. Kun He and Dr. Tie-Yan Liu. Before that, he got the B.S. degree from School of Artificial Intelligence and Automation, HUST in 2021. He currently is a member of AI4Science Research Project, mentored by Dr. Lijun Wu. He also works closely with Qizhi Pei.

His researches focus on AI4science, geometric deep learning, and multi-modal learning for biomolecule.

🔥 News

• 2024.05:  🎉🎉 BioT5+ is accepted by ACL 2024 (Findings). Thanks for all collaborators!
• 2023.10:  🎉🎉 BioT5 is accepted by EMNLP 2023. Thanks for all collaborators!
• 2023.09:  🎉🎉 FABind is accepted by NeurIPS 2023. Thanks for all collaborators!
• 2023.08:  🎉🎉 ABGNN is accepted by KDD 2023. Thanks for all collaborators!
• 2023.02:  🎉🎉 NAGphormer is accepted by ICLR 2023. Thanks for all collaborators!

📝 Publications

(“*”: equal contribution; “†”: correspondence)

NeurIPS 2023

FABind: Fast and Accurate Protein-Ligand Binding
Qizhi Pei^* , Kaiyuan Gao^* , Lijun Wu^† , Jinhua Zhu, Yingce Xia, Shufang Xie, Tao Qin, Kun He, Tie-Yan Liu, Rui Yan^†
Project | |

KDD 2023

Pre-training Antibody Language Models for Antigen-Specific Computational Antibody Design
Kaiyuan Gao, Lijun Wu^† , Jinhua Zhu, Tianbo Peng, Yingce Xia, Liang He, Shufang Xie, Tao Qin, Haiguang Liu, Kun He, Tie-Yan Liu
Code |

ICLR 2023

NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs
Jinsong Chen^* , Kaiyuan Gao^* , Gaichao Li, Kun He^†
Code |

Arxiv 2024

FABind+: Enhancing Molecular Docking through Improved Pocket Prediction and Pose Generation
Kaiyuan Gao^* , Qizhi Pei^* , Gongbo Zhang, Jinhua Zhu, Tao Qin, Kun He, Lijun Wu^†
Code |

Arxiv 2023

Examining User-Friendly and Open-Sourced Large GPT Models: A Survey on Language, Multimodal, and Scientific GPT Models
Kaiyuan Gao^* , Sunan He^* , Zhenyu He^* , Jiacheng Lin^* , Qizhi Pei^* , Jie Shao^* , Wei Zhang^*
Code |

• EMNLP 2023BioT5: Enriching Cross-modal Integration in Biology with Chemical Knowledge and Natural Language Associations
  Qizhi Pei, Wei Zhang, Jinhua Zhu, Kehan Wu, Kaiyuan Gao, Lijun Wu, Yingce Xia, Rui Yan
  Code | | |

• ACL 2024 (Findings)BioT5+: Towards Generalized Biological Understanding with IUPAC Integration and Multi-task Tuning
  Qizhi Pei, Lijun Wu, Kaiyuan Gao, Xiaozhuan Liang, Yin Fang, Jinhua Zhu, Shufang Xie, Tao Qin, Rui Yan
  Code |

• Leveraging Biomolecule and Natural Language through Multi-Modal Learning: A Survey
  Qizhi Pei, Lijun Wu, Kaiyuan Gao, Jinhua Zhu, Yue Wang, Zun Wang, Tao Qin, Rui Yan
  Project |