I am a Staff Software Dev Engineer at Apple in the area among computational mechanics, material physics, and machine learning. My research interests are centered on developing theories and methods to solve challenging multiscale, multiphysics, and design problems in modern computer engineering and advanced manufacturing.
Previously, I worked as a senior research scientist in the computational and multiscale mechanics group at ANSYS LST, where I led a team of PhD students and developers in scientific machine learning research and the development of LS-DYNA multiscale packages for various industrial material systems.
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
Northwestern University
B.E. in Micro-Electro-Mechanical System Engineering, 2012
Tsinghua University (China)