Building intelligent systems for scientific discovery构建面向科学发现的智能系统

Zhixiang Ren is currently Chief AI Scientist at Shanghai Smart Logic Technology, a doctoral supervisor at Tsinghua University and the Southern University of Science and Technology, and a Shenzhen-recognized High-Level Talent. His research focuses on AI for Science, scientific foundation models and agents, and AI-driven drug discovery. He has published more than 80 papers in leading journals, including Nature, Science, and Nature Machine Intelligence. His work has received over 10,000 citations with an h-index of 32. He holds 20 granted invention patents and 5 registered software copyrights. His honors include the 2025 First Prize of the State Science and Technology Progress Award, the 2024 AI Innovation Award, and the 2024 Special Prize of Guangdong Province Science and Technology Progress Award. He has led the development of 1 international standard and 2 industry standards in intelligent computing. He has also led the performance benchmarking of ultra-large-scale AI computing clusters, with his teams topping the ranking of highest-performing AI computing systems for several consecutive years. He currently serves as an Associate Editor for Big Data Mining and Analytics and CAAI Artificial Intelligence Research, as well as a program committee member for KDD and other international conferences. He is also a long-standing reviewer for journals in the Nature Portfolio and the IEEE Transactions series.任智祥，现任思朗科技 AI 首席科学家，清华大学与南方科技大学博导，深圳市高层次人才。主要研究领域为科学智能（AI for Science），AI 药物研发，科学大模型与智能体等。累计在 Nature/Science/Nature Machine Intelligence 等期刊上发表论文 80 余篇，谷歌学术引用 10000 余次（H-index 32），获得国家发明专利授权 20 项，软著 5 项。曾获 2025 年国家科技进步一等奖，2024 年 AI 创新奖（祖冲之奖），2023 年广东省科技进步特等奖。主导制定了智能计算领域 1 项国际标准与 2 项行业标准。带领团队进行超大规模 AI 集群的智能算力评测工作，并连续多年获得“世界人工智能算力性能 500 排行榜”冠军。现任《Big Data Mining and Analytics》、《Frontiers in Big Data》等期刊副主编，KDD 等国际会议程序委员会委员, 并长期担任 Nature 系列子刊与 IEEE Trans 期刊审稿人。

Recent Papers近期论文

10
  1. BioinformaticsPublished已发表

    The limits of bio-molecular modeling with large language models: a cross-scale evaluation

    Yaxin Xu, Yue Zhou, Tianyu Zhao, Zhengyu Ma, Fengwei An, Zhixiang Ren

    DOI ↗Code ↗代码 ↗
    BibTeX
    @article{Xu_2026,
  title={The limits of bio-molecular modeling with large language models: a cross-scale evaluation},
  volume={42},
  ISSN={1367-4811},
  url={http://dx.doi.org/10.1093/bioinformatics/btag550},
  DOI={10.1093/bioinformatics/btag550},
  number={8},
  journal={Bioinformatics},
  publisher={Oxford University Press (OUP)},
  author={Xu, Yaxin and Zhou, Yue and Zhao, Tianyu and Ma, Zhengyu and An, Fengwei and Ren, Zhixiang},
  editor={Uhlmann, Virginie},
  year={2026},
  month=July
}
  2. bioRxivPreprint预印本

    Phenotype-driven de novo molecular design from gene expression signatures

    Yaxin Xu, Taojie Kuang, Shuang Ge, Haomin Wu, Mingqing Wang, Huan Xu, Fengwei An, Zhengyu Ma, Qiang Cheng, Zhixiang Ren

    bioRxiv ↗Code ↗代码 ↗
    BibTeX
    @article{Xu_2026,
  title={Phenotype-driven de novo molecular design from gene expression signatures},
  url={http://dx.doi.org/10.64898/2026.07.21.739736},
  DOI={10.64898/2026.07.21.739736},
  publisher={openRxiv},
  author={Xu, Yaxin and Kuang, Taojie and Ge, Shuang and Wu, Haomin and Wang, Mingqing and Xu, Huan and An, Fengwei and Ma, Zhengyu and Cheng, Qiang and Ren, Zhixiang},
  year={2026},
  month=July
}
  3. bioRxivPreprint预印本

    Improving Variant Effect Prediction by Steering Sparse Mechanistic Features in Protein Language Models

    Mingqing Wang, Meng Yuan, Athanasios V. Vasilakos, Yonghong He, Zhixiang Ren

    bioRxiv ↗
    BibTeX
    @article{Wang_2026,
  title={Improving Variant Effect Prediction by Steering Sparse Mechanistic Features in Protein Language Models},
  url={http://dx.doi.org/10.64898/2026.05.12.724472},
  DOI={10.64898/2026.05.12.724472},
  publisher={openRxiv},
  author={Wang, Mingqing and Yuan, Meng and Vasilakos, Athanasios V. and He, Yonghong and Ren, Zhixiang},
  year={2026},
  month=May
}
  4. arXivPreprint预印本

    Learning Protein Structure-Function Relationships through Knowledge-guided Representation Decomposition

    Mingqing Wang, Zhiwei Nie, Athanasios V. Vasilakos, Yonghong He, Zhixiang Ren

    arXiv ↗Code ↗代码 ↗
    BibTeX
    @misc{Wang2026Learning,
  title = {Learning Protein Structure-Function Relationships through Knowledge-guided Representation Decomposition},
  author = {Mingqing Wang and Zhiwei Nie and Athanasios V. Vasilakos and Yonghong He and Zhixiang Ren},
  year = {2026},
  eprint = {2605.23960},
  archivePrefix = {arXiv},
  primaryClass = {q-bio.BM}
}
  5. J. Chem. Inf. Model.Published已发表

    Pseudodata-Guided Invariant Representation Learning Boosts the Out-of-Distribution Generalization in Enzymatic Kinetic Parameter Prediction

    Haomin Wu, Zhiwei Nie, Hongyu Zhang, Zhixiang Ren

    DOI ↗
    BibTeX
    @article{Wu_2026,
  title={Pseudodata-Guided Invariant Representation Learning Boosts the Out-of-Distribution Generalization in Enzymatic Kinetic Parameter Prediction},
  volume={66},
  ISSN={1549-960X},
  url={http://dx.doi.org/10.1021/acs.jcim.5c03204},
  DOI={10.1021/acs.jcim.5c03204},
  number={9},
  journal={Journal of Chemical Information and Modeling},
  publisher={American Chemical Society (ACS)},
  author={Wu, Haomin and Nie, Zhiwei and Zhang, Hongyu and Ren, Zhixiang},
  year={2026},
  month=Apr,
  pages={5068–5077}
}
  6. arXivPreprint预印本

    Enhanced Drug-drug Interaction Prediction Using Adaptive Knowledge Integration

    Pengfei Liu, Jun Tao, Zhixiang Ren

    arXiv ↗Code ↗代码 ↗
    BibTeX
    @misc{Liu2026Enhanced,
  title = {Enhanced Drug-drug Interaction Prediction Using Adaptive Knowledge Integration},
  author = {Pengfei Liu and Jun Tao and Zhixiang Ren},
  year = {2026},
  eprint = {2603.12885},
  archivePrefix = {arXiv},
  primaryClass = {cs.LG}
}
  7. arXivPreprint预印本

    A Multi-task Large Reasoning Model for Molecular Science

    Pengfei Liu, Shuang Ge, Jun Tao, Zhixiang Ren

    arXiv ↗Code ↗代码 ↗
    BibTeX
    @misc{Liu2026Multitask,
  title = {A Multi-task Large Reasoning Model for Molecular Science},
  author = {Pengfei Liu and Shuang Ge and Jun Tao and Zhixiang Ren},
  year = {2026},
  eprint = {2603.12808},
  archivePrefix = {arXiv},
  primaryClass = {cs.LG}
}
  8. bioRxivPreprint预印本

    Prototype-based continual cell-type annotation reveals cellular state transitions in expanding single-cell atlases

    Shuang Ge, Qiming He, Yiming Ren, Yaxin Xu, Mingqing Wang, Zhiwei Nie, Huan Xu, Qiang Cheng, Shuqing Sun, Zhixiang Ren

    bioRxiv ↗Code ↗代码 ↗
    BibTeX
    @article{Ge_2026,
  title={Prototype-based continual cell-type annotation reveals cellular state transitions in expanding single-cell atlases},
  url={http://dx.doi.org/10.64898/2026.03.05.709973},
  DOI={10.64898/2026.03.05.709973},
  publisher={openRxiv},
  author={Ge, Shuang and He, Qiming and Ren, Yiming and Xu, Yaxin and Wang, Mingqing and Nie, Zhiwei and Xu, Huan and Cheng, Qiang and Sun, Shuqing and Ren, Zhixiang},
  year={2026},
  month=Mar
}
  9. Eng. Appl. Artif. Intell.Published已发表

    A self-feedback knowledge elicitation approach for chemical reaction predictions

    Pengfei Liu, Jun Tao, Zhixiang Ren

    DOI ↗Code ↗代码 ↗
    BibTeX
    @article{Liu_2025,
  title={A self-feedback knowledge elicitation approach for chemical reaction predictions},
  volume={156},
  ISSN={0952-1976},
  url={http://dx.doi.org/10.1016/j.engappai.2025.111112},
  DOI={10.1016/j.engappai.2025.111112},
  journal={Engineering Applications of Artificial Intelligence},
  publisher={Elsevier BV},
  author={Liu, Pengfei and Tao, Jun and Ren, Zhixiang},
  year={2025},
  month=Sept,
  pages={111112}
}
  10. Eng. Appl. Artif. Intell.Published已发表

    Deep learning methods for protein representation and function prediction: A comprehensive overview

    Mingqing Wang, Zhiwei Nie, Yonghong He, Athanasios V. Vasilakos, Qiang (Shawn) Cheng, Zhixiang Ren

    DOI ↗
    BibTeX
    @article{Wang_2025,
  title={Deep learning methods for protein representation and function prediction: A comprehensive overview},
  volume={155},
  ISSN={0952-1976},
  url={http://dx.doi.org/10.1016/j.engappai.2025.110977},
  DOI={10.1016/j.engappai.2025.110977},
  journal={Engineering Applications of Artificial Intelligence},
  publisher={Elsevier BV},
  author={Wang, Mingqing and Nie, Zhiwei and He, Yonghong and Vasilakos, Athanasios V. and Cheng, Qiang (Shawn) and Ren, Zhixiang},
  year={2025},
  month=Sept,
  pages={110977}
}

Experience经历

  1. Chief AI ScientistAI 首席科学家

    SmartLogic Tech · Shanghai思朗科技 · 上海

  2. Research Scientist · Ph.D. Supervisor研究员 · 博士生导师

    Peng Cheng Laboratory鹏城国家实验室

    Head, AI for Science Lab科学智能研究室负责人

  3. Associate Research Fellow特聘副研究员

    Sun Yat-sen University中山大学

  4. Postdoctoral Fellow博士后研究员

    University of New Mexico美国新墨西哥大学

  5. Ph.D. · Computational Physics & Machine Learning理学博士 · 计算物理与机器学习

    University of New Mexico美国新墨西哥大学

Services & Honors学术服务与荣誉

Editorial编辑工作
Associate Editor · Big Data Mining and Analytics · CAAI Artificial Intelligence Research · Frontiers in Big Data《Big Data Mining and Analytics》 · 《CAAI Artificial Intelligence Research》 · 《Frontiers in Big Data》 · 副主编
Reviewing评审工作
KDD Program Committee · Reviewer for Nature portfolio journals · Reviewer for IEEE Transactions journalsKDD 程序委员会委员 · Nature 系列期刊审稿人 · IEEE Transactions 期刊审稿人
Awards代表性荣誉
2025 National Science and Technology Progress Award, First Prize · 2024 AI Innovation Award · Zuchongzhi Award · 2023 Guangdong Science and Technology Progress Award, Special Prize2025 国家科技进步一等奖 · 2024 AI 创新奖（祖冲之奖） · 2023 广东省科技进步特等奖