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Tao Qin
Tao Qin

Vice President of Zhongguancun Academy

Dr. Tao Qin is the Vice President of Zhongguancun Academy (ZGCA) and oversees its AI4science division. He earned both his bachelor's and PhD degrees from Tsinghua University. Before joining ZGCA, he served as a partner research manager at Microsoft Research AI4Science Lab and led the Microsoft Research AI4Science Asia team. His team proposed dual learning in 2016, which helped Microsoft achieve human parity in the 2018 Chinese-English news translation and win 8 tasks at the WMT2019. In 2019, his team developed the most efficient speech synthesis model at the time, FastSpeech, achieving 100x acceleration and becoming a key component supporting hundreds of languages and voices in Microsoft's Azure cloud service. In the same year, his team developed the most powerful Mahjong AI ever, Suphx, achieving 10 DAN on the Tenhou platform, with a stable rank significantly superior to top human professionals. In 2020, he published the academic monograph 'Dual Learning'. Recently he focuses on AI for scientific discovery, including science foundation models, drug discovery, materials design, biology research, etc.

Work & Education Experiences
Sept. 1999 – July. 2003, BS, Dept. of Electronic Engineering, Tsinghua University
Sept. 2003 – July 2008, PhD., Dept. of Electronic Engineering, Tsinghua University
July 2008 – July 2022, Senior Principal Researcher/Manager at Microsoft Research Asia
July 2022 – July 2025, Partner Researcher/Manager at Microsoft Research AI4Science
July 2025 – present, Vice President at Zhongguancun Academy

 

Selected Publications

  • Haoran Sun, Liang He, Pan Deng, Guoqing Liu, Zhiyu Zhao, Yuliang Jiang, Chuan Cao, Fusong Ju, Lijun Wu, Haiguang Liu, Tao Qin, Tie-Yan Liu. Accelerating protein engineering with fitness landscape modelling and reinforcement learning. Nature Machine Intelligence 2025.
  • Yunyang Li, Lin Huang, Zhihao Ding, Xinran Wei, Chu Wang, Han Yang, Zun Wang, Chang Liu, Yu Shi, Peiran Jin, Jia Zhang, Mark Gerstein, Tao Qin. E2Former: An Efficient and Equivariant Transformer with Linear-Scaling Tensor Products. NeurIPS 2025.
  • Xiaohua Wang, Kaitao Song, Xu Tan, Huiqiang Jiang, Chengruidong Zhang, Yongliang Shen, Cen LU, Zihao Li, Zifan Song, Caihua Shan, Yansen Wang, Kan Ren, Xiaoqing Zheng, Tao Qin, Yuqing Yang, Dongsheng Li, Lili Qiu. Chain-of-Model Learning for Language Model. NeurIPS 2025.
  • Zeqian Ju, Dongchao Yang, Jianwei Yu, Kai Shen, Yichong Leng, Zhengtao Wang, Songxiang Liu, Xinyu Zhou, Tao Qin, Xiangyang Li, Xu Tan. High-Quality Zero-Shot Podcast Generation. NeurIPS 2025.
  • NatureLM: Deciphering the Language of Nature for Scientific Discovery. arXiv 2025.
  • Mingqian Ma, Guoqing Liu, Chuan Cao, Pan Deng, Tri Dao, Albert Gu, Peiran Jin, Zhao Yang, Yingce Xia, Renqian Luo, Pipi Hu, Zun Wang, Yuan-Jyue Chen, Haiguang Liu, Tao Qin. HybriDNA: A Hybrid Transformer-Mamba2 Long-Range DNA Language Model. arXiv 2025.
  • Kehan Wu, Yingce Xia, Pan Deng, Renhe Liu, Yuan Zhang, Han Guo, Yumeng Cui, Qizhi Pei, Lijun Wu, Shufang Xie, Si Chen, Xi Lu, Song Hu, Jinzhi Wu, Chi-Kin Chan, Shawn Chen, Liangliang Zhou, Nenghai Yu, Enhong Chen, Haiguang Liu, Jinjiang Guo, Tao Qin, Tie-Yan Liu. Target-aware Molecule Generation for Drug Design Using a Chemical Language Model. Nature Communications 2024.
  • Qizhi Pei, Lijun Wu, Jinhua Zhu, Yingce Xia, Shufang Xie, Tao Qin, Haiguang Liu, Rui Yan. Breaking the Barriers of Data Scarcity in Drug-Target Affinity Prediction. Briefings in Bioinformatics 2023.
  • Jinhua Zhu, Yingce Xia, Chang Liu, Lijun Wu, Shufang Xie, Yusong Wang, Tong Wang, Tao Qin, Wengang Zhou, Houqiang Li, Haiguang Liu, Tie-Yan Liu. Direct Molecular Conformation Generation. TMLR 2022.
  • Renqian Luo, Liai Sun, Yingce Xia, Tao Qin, Sheng Zhang, Hoifung Poon, Tie-Yan Liu. BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining. Briefings in Bioinformatics.
  • Lijun Wu, Chengcan Yin, Jinhua Zhu, Zhen Wu, Liang He, Yingce Xia, Shufang Xie, Tao Qin, Tie-Yan Liu. SPRoBERTa: Protein Embedding Learning with Local Fragment Modeling. Briefings in Bioinformatics.
  • Jinhua Zhu, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu. Unified 2D and 3D Pre-Training of Molecular Representations. KDD 2022.
  • Shufang Xie, Peng Han, Yingce Xia, Lijun Wu, Tao Qin, Chenjuan Guo, Bin Yang, Rui Yan. RetroGraph: Retrosynthetic Planning with Graph Search. KDD 2022.
  • Yutai Hou, Yingce Xia, Lijun Wu, Shufang Xie, Yang Fan, Jinhua Zhu, Tao Qin, Tie-Yan Liu, Discovering Drug-Target Interaction Knowledge from Biomedical Literature. Bioinformatics, 2022.
  • Yang Fan, Yingce Xia, Jinhua Zhu, Lijun Wu, Shufang Xie, Tao Qin. Back Translation for Molecule Generation. Bioinformatics, 2021.
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