Yongchao Yang

Yongchao Yang


  • 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.

Research Interests

  • Structural dynamics
  • System identification
  • Structural health monitoring
  • Non-destructive evaluation
  • High-resolution sensing/imaging
  • Machine learning
  • Computer vision