Yongchao Yang

Biography

Dr. Yang’s expertise is in structural dynamics, experimental mechanics, and system identification. His recent research aims to develop "physics-guided" machine learning methodology for high-fidelity modeling, identification, and characterization of complex structural and system behaviors. In particular, his latest projects focus on developing full-field, high-resolution sensing/imaging methods for detecting subtle structural and material defects through optical and acoustic (ultrasonic) tools, combining approaches from computer vision and machine (deep) learning. These commonly involve processing very large-scale images/videos and sensor array "big" data, e.g., millions of pixels from a digital camera where every pixel is considered as a "virtual" sensor. His work strives to advance applications for structural health monitoring, non-destructive evaluations, dynamical system identification and control in the broad areas of cyber-physical systems.

Before joining Michigan Tech, Dr. Yang was a staff scientist at Argonne National Laboratory (2018-2019), after a Director's Funded Postdoctoral Fellowship at Los Alamos National Laboratory (2015-2017). He obtained his PhD from Rice University in 2014 and bachelor's from Harbin Institute of Technology in 2010, both in structural engineering.