Han Wang (王涵) Ph.D.

Laboratory of Computational Physics

Institute of Applied Physics and Computational Mathematics

Huayuan Road 6
100088 Beijing, China

Email:  wang_han(AT)iapcm(DOT)ac(DOT)cn

Curriculum Vitae

History

• Scientist, Institute of Applied Physics and Computational Mathematics, Beijing, 2018-
• Scientist, CAEP Software Center for High Performance Numerical Simulation, Institute of Applied Physics and Computational Mathematics, Beijing, 2014-2018
• Postdoctoral researcher, Freie Universität Berlin, Germany, 2011-2014
• Ph.D., Computational mathematics, Peking University, P.R. China, 2006-2011
• B.S., Computational mathematics, Peking University, P.R. China, 2002-2006

Research

• Multiscale modeling and simulation.


• Numerical analysis and fast algorithms for molecular dynamics.

Software

• DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics


• DP-GEN: The deep potential generator.


• dpdata: A python tool for data format conversion.

Selected Publications

A full list of publications can be found here

• Dongdong Wang, Yanze Wang, Junhan Chang, Linfeng Zhang, Han Wang, Weinan E
  Efficient sampling of high-dimensional free energy landscapes using adaptive reinforced dynamics
  Nature Computational Science, 2, 20-29 (2021).


• Linfeng Zhang, Han Wang, Roberto Car and Weinan E
  The Phase Diagram of a Deep Potential Water Model
  Physical Review Letters, 126(23), 236001 (2021).


• Yixiao Chen, Linfeng Zhang*, Han Wang*, and Weinan E
  DeePKS: A Comprehensive Data-Driven Approach toward Chemically Accurate Density Functional Theory
  Journal of Chemical Theory and Computation, 17(1) 170–181 (2021).


• Weile Jia, Han Wang, Mohan Chen, Denghui Lu, Lin Lin, Roberto Car, Weinan E and Linfeng Zhang
  Pushing the limit of molecular dynamics with ab initio accuracy to 100 million atoms with machine learning
  SC'20: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, 5 1-14 (2020).


• Yuzhi Zhang, Haidi Wang, Weijie Chen, Jinzhe Zeng, Linfeng Zhang*, Han Wang*, Weinan E*
  DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models
  Computer Physics Communications, 253, 107206 (2020).


• Linfeng Zhang, De-Ye Lin, Han Wang*, Roberto Car and Weinan E*
  Active learning of uniformly accurate interatomic potentials for materials simulation
  Physical Review Materials, 3, 023804 (2019).


• Linfeng Zhang, Han Wang*, Weinan E*,
  Reinforced dynamics for enhanced sampling in large atomic and molecular systems
  The Journal of Chemical Physics, 148, 124113 (2018).


• Linfeng Zhang, Jiequn Han, Han Wang*, Roberto Car, Weinan E*,
  Deep Potential Molecular Dynamics: a scalable model with the accuracy of quantum mechanics
  Physical Review Letters, 120, 143001 (2018).


• Han Wang*, Jun Fang, Xingyu Gao,
  The optimal particle-mesh interpolation basis
  The Journal of Chemical Physics, 147, 124107 (2017).


• Han Wang*, Xingyu Gao and Jun Fang
  Multiple Staggered Mesh Ewald: Boosting the Accuracy of the Smooth Particle Mesh Ewald Method
  Journal of Chemical Theory and Computation, 12(11), 5596-5608 (2016).


• Han Wang* and Christof Schütte*
  Building Markov State Models for Periodically Driven Non-Equilibrium Systems
  Journal of Chemical Theory and Computing, 11(4) 1819-1831 (2015).


• Han Wang, Carsten Hartmann, Christof Schütte, and Luigi Delle Site*
  Grand-canonical-like molecular-dynamics simulations by using an adaptive-resolution technique
  Physical Review X, 3, 011018 (2013).