曾晋哲
Email: jinzhe.zeng@ustc.edu.cn
办公地址：苏州高等研究院唯真楼403
个人主页：https://faculty.ustc.edu.cn/jinzhezeng/
研究方向： AI for Computational Chemistry、复杂化学体系分子动力学、深度学习势能模型
个人简介：曾晋哲，2019年本科毕业于华东师范大学化学专业，2025年1月获美国罗格斯新泽西州立大学（Rutgers University）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。截至2025年3月，发表SCI论文17篇，其中第一/共一作者8篇，发表于Nat. Commun., J. Chem. Theory Comput., J. Chem. Phys.等期刊，被引1600余次，h-index达14。主导DeePMD-kit等科学计算软件的设计和开发。
主要论著：
[1] Jinzhe Zeng, Duo Zhang, Denghui Lu, Pinghui Mo, Zeyu Li, Yixiao Chen, Marián Rynik, Li’ang Huang, Ziyao Li, Shaochen Shi, Yingze Wang, Haotian Ye, Ping Tuo, Jiabin Yang, Ye Ding, Yifan Li, Davide Tisi, Qiyu Zeng, Han Bao, Yu Xia, Jiameng Huang, Koki Muraoka, Yibo Wang, Junhan Chang, Fengbo Yuan, Sigbjørn Løland Bore, Chun Cai, Yinnian Lin, Bo Wang, Jiayan Xu, Jia-Xin Zhu, Chenxing Luo, Yuzhi Zhang, Rhys E. A. Goodall, Wenshuo Liang, Anurag Kumar Singh, Sikai Yao, Jingchao Zhang, Renata Wentzcovitch, Jiequn Han, Jie Liu, Weile Jia, Darrin M. York, Weinan E, Roberto Car, Linfeng Zhang, Han Wang*, DeePMD-kit v2: A software package for Deep Potential models, The Journal of Chemical Physics, 2023, 159, 054801.
[2] Jinzhe Zeng, Yujun Tao, Timothy J. Giese, Darrin M. York*, Modern semiempirical electronic structure methods and machine learning potentials for drug discovery: conformers, tautomers and protonation states, The Journal of Chemical Physics, 2023, 158, 124110.
[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, Liqun Cao, Tong Zhu*. Chapter 12 - Neural network potentials. in Pavlo O. Dral (Eds.), Quantum Chemistry in the Age of Machine Learning (pp. 279-294), Elsevier, 2023.
[5] Timothy J. Giese#, ̧Jinzhe Zeng#, Sölen Ekesan, Darrin M. York*, Combined QM/MM, Machine Learning Path Integral Approach to Compute Free Energy Profiles and Kinetic Isotope Effects in RNA Cleavage Reactions, Journal of Chemical Theory and Computation, 2022, 18 (7), 4304-4317.
[6] 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.
[7] Jinzhe Zeng, Linfeng Zhang*, Han Wang*, Tong Zhu*, Exploring the Chemical Space of Linear Alkanes Pyrolysis via Deep Potential GENerator, Energy & Fuels, 2021, 35 (1), 762-769.
[8] 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.
[9] Jinzhe Zeng#, Liqun Cao#, Chih-Hao Chin*, Haisheng Ren, John Z. H. Zhang*, Tong Zhu*, ReacNetGenerator: an automatic reaction network generator for reactive molecular dynamics simulations, Phys. Chem. Chem. Phys., 2020, 22 (2), 683–691.