曾晋哲
邮 件： jinzhe.zeng@ustc.edu.cn
所属单位：人工智能与数据科学学院
个人主页： https://faculty.ustc.edu.cn/jinzhezeng
主要研究方向： 人工智能驱动的计算化学研究
中国科学技术大学人工智能与数据科学学院预聘副教授，博士生导师。2019年7月获华东师范大学化学专业学士学位，2025年1月获罗格斯新泽西州立大学化学与化学生物学专业博士学位。2025年2月加入中国科学技术大学人工智能与数据科学学院，任预聘副教授。
2024年获国家优秀自费留学生奖学金。截至2026年3月，发表SCI论文25篇，其中第一/共一/通讯作者13篇，发表于Nat. Commun., J. Chem. Theory Comput.等期刊，h-index指数为19，总被引超过2900次。主持DeePMD-kit等人工智能驱动的科学计算软件的设计和开发。
教授课程：
1. 研究生课程《人工智能与分子科学》
近几年代表论著：
[1] Jinzhe Zeng*, Xingliang Peng, Yong-Bin Zhuang, Haidi Wang, Fengbo Yuan, Duo Zhang, Renxi Liu, Yingze Wang, Ping Tuo, Yuzhi Zhang, Yixiao Chen, Yifan Li, Cao Thang Nguyen, Jiameng Huang, Anyang Peng, Marián Rynik, Wei-Hong Xu, Zezhong Zhang, Xu-Yuan Zhou, Tao Chen, Jiahao Fan, Wanrun Jiang, Bowen Li, Denan Li, Haoxi Li, Wenshuo Liang, Ruihao Liao, Liping Liu, Chenxing Luo, Logan Ward, Kaiwei Wan, Junjie Wang, Pan Xiang, Chengqian Zhang, Jinchao Zhang, Rui Zhou, Jia-Xin Zhu, Linfeng Zhang*, Han Wang*, dpdata: A Scalable Python Toolkit for Atomistic Machine Learning Data Sets, J. Chem. Inf. Model., 2025, 65, 11497-11504.
[2] Jinzhe Zeng*, Duo Zhang, Anyang Peng, Xiangyu Zhang, Sensen He, Yan Wang, Xinzijian Liu, Hangrui Bi, Yifan Li, Chun Cai, Chengqian Zhang, Yiming Du, Jia-Xin Zhu, Pinghui Mo, Zhengtao Huang, Qiyu Zeng, Shaochen Shi, Xuejian Qin, Zhaoxi Yu, Chenxing Luo, Ye Ding, Yun-Pei Liu, Ruosong Shi, Zhenyu Wang, Sigbjørn Løland Bore, Junhan Chang, Zhe Deng, Zhaohan Ding, Siyuan Han, Wanrun Jiang, Guolin Ke, Zhaoqing Liu, Denghui Lu, Koki Muraoka, Hananeh Oliaei, Anurag Kumar Singh, Haohui Que, Weihong Xu, Zhangmancang Xu, Yong-Bin Zhuang, Jiayu Dai, Timothy J. Giese, Weile Jia, Ben Xu, Darrin M. York, Linfeng Zhang*, Han Wang*, DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning Potentials, Journal of Chemical Theory and Computation, 2025, 21, 9, 4375-4385.
[3] Jinzhe Zeng, Yujun Tao, Timothy J. Giese, Darrin M. York*, QDπ: A Quantum Deep Potential Interaction Model for Drug Discovery, Journal of Chemical Theory and Computation, 2023, 19, 4, 1261-1275.
[4] Jinzhe Zeng, Timothy J. Giese, ̧Sölen Ekesan, Darrin M. York*, Development of Range-Corrected Deep Learning Potentials for Fast, Accurate Quantum Mechanical/Molecular Mechanical Simulations of Chemical Reactions in Solution, Journal of Chemical Theory and Computation, 2021, 17 (11), 6993-7009.
[5] Jinzhe Zeng, Liqun Cao, Mingyuan Xu, Tong Zhu*, John Z. H. Zhang*, Complex reaction processes in combustion unraveled by neural network-based molecular dynamics simulation, Nature Communications, 2020, 11, 5713.