- MEEM 926
- Assistant Professor, Mechanical Engineering-Engineering Mechanics
- PhD, Structural Engineering, Rice University
- BE, Structural Engineering, Harbin Institute of Technology
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.
- Structural dynamics
- System identification
- Structural health monitoring
- Non-destructive evaluation
- High-resolution sensing/imaging
- Machine learning
- Computer vision
- "Making physical sense of machine learning: full-field, high-resolution imaging of structural dynamics", Defense Advanced Research Projects Agency (DARPA), 2018-2020.
- "Neuromorphic Event-Driven Dynamic Vision Sensing and Processing: Silicon Retina Imaging", Argonne National Lab Directed Research and Development, 2018.
- "Low-cost High-resolution Sensing and Health Monitoring of Urban Infrastructure", Los Alamos Directed Research and Development, 2015 - 2017