I am a senior research scientist at Livermore Software Technology in the emerging area among computational mechanics, material physics, and machine learning. My research is centered on developing theories and methods to solve challenging multiscale and multiphysics problems in modern materials engineering and advanced manufacturing.
My recent work on deep material network presents a new way of embedding physics into a network model for large-scale multiscale simulation and materials design. The key features are the physics-based building block with interpretable fitting parameters, extrapolation capability for material and geometric nonlinearities with only linear elastic training data, and efficient online inference. More details can be found in my lectures for 2020 ML-SIG and USNCCM15 short course.
Ph.D. in Theoretical and Applied Mechanics, 2017
B.E. in Micro-Electro-Mechanical System Engineering, 2012
Tsinghua University (China)