Eric Lindgren

Research

Eric’s research is concerned with the development and application of a computational framework that combines atomic-scale modeling, machine learning, and neutron scattering data in order to extract structural and dynamical information of liquid chromophores in both their ground and excited states. His Ph.D. project is part of the SwedNess research school.

Education

• 2021: M.Sc. in Physics; Chalmers University of Technology
  Saliency mapping of RS-fMRI data in GCNs for sex and brain age prediction
• 2019: B.Sc. in Applied Physics; Chalmers University of Technology

Publications

• GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations Permalink
  Z. Fan, Y. Wang, P. Ying, K. Song, J. Wang, Y. Wang, Z. Zeng, K. Xu, E. Lindgren, J. M. Rahm, A. J. Gabourie, J. Liu, H. Dong, J. Wu, Y. Chen, Z. Zhong, J. Sun, P. Erhart, Y. Su, and T. Ala-Nissila
  arXiv:2205.10046 (2022)