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Curriculum Vitae

Current State

Li Jichen

University of Science and Technology of China
No.96, JinZhai Road Baohe District, Hefei, Anhui, 230026, P.R.China
lijichen365@mail.ustc.edu.cn

Education Background

  • Aug 2020-Jun 2023

    • University of Science and Technology of China, Hefei, Anhui, China
    • Major: Chemistry, Master of science
  • Sept 2016-Jun 2020

    • University of Science and Technology of Qingdao, Qingdao, Shandong, China
    • Major: Chemistry, Bachelor of Science

Research Experience

  • Feb 2022-Now

    • Fabrication of Ionomer Colloids and Vesicle via Polyelectrolyte Complexation
    • Study on the Behavior of Polyelectrolytes
  • Oct 2021-Now

    • Work as an intern in DP Technonlogy.
    • Development of Differentiable Molecular Force Field Framework

Publications

  • Wang X, Li J, Yang L, Chen F, Wang Y, Chang J, et al. DMFF: An Open-Source Automatic Differentiable Platform for Molecular Force Field Development and Molecular Dynamics Simulation, ChemRxiv, 2022, 10.26434/chemrxiv-2022-2c7gv

  • Yang, L.; Li, J.; Chen, F.; Yu, K.*, Transferrable Range-Separated Force Field for Water: Combining the Power of Both Physically-Motivated Models and Machine Learning Techniques, J. Chem. Phys., 2022, 10.1063/5.0128780

  • Shafat M.; Li, J.(co-first), Extending and Modifying LAMMPS Writing Your Own Source Code, PACKT, 2021, Amazon

  • Song, J.; Li, J.; Zhibo Li*, Molecular Dynamics Simulations of Uniaxial Deformation of Bimodal Polyethylene Melts, Polymer, 2021, 10.1016/j.polymer.2020.123210

  • Song, J., Li, J., Chan, H. S., Small-angle X-ray scattering signatures of conformational heterogeneity and homogeneity of disordered protein ensembles, J. Phys. Chem. B, 2021, 10.1021/acs.jpcb.1c02453

Software Projects

  • DMFF Jax-based differantial molecular force field framework

  • molpy A data structure used to describe molecules in computational chemistry

  • flowie A lightweight workflow to manage computation tasks and analysis jobs

Skills

  • Background: polymer physics, rheology and statistical physics
  • Tools: LAMMPS, OpenMM, Jax-MD, Gaussian, CP2K
  • Language: Python, C++, Fortran
  • Framework: CUDA, MPI, TensorFlow/PyTorch/JAX, Qt
  • Experience: secondary development of LAMMPS