Wenyuan Liao

Dr. Wenyuan Liao

Background

Educational Background

Ph.D. Mathematics, Mississippi State University, 2003

Research

Areas of Research

Inverse modeling and industrial applications
Wave equation-based inversion and applications

I have long been dedicated to applying full waveform inversion to seismic imaging, and I have recently begun extending this approach to the inversion of medical data to provide high-resolution images for medical diagnosis.

High performance computing and scientific computation
Numerical methods for PDEs
Numerical methods and applications to geophysics
Deep Neural Networks Method for PDEs and Inverse Problems

Deep neural networks provide a universally adaptive function approximation framework. I am interested in integrating them with full waveform inversion and, based on various convenient development platforms (such as TensorFlow, PyTorch, etc.), developing and researching fast, efficient, and stable parameter estimation and imaging algorithms as well as software packages.

Courses

Course number Course title Semester
MATH 277 Multivariable Calculus for Engineers and Scientists Winter 2026
MATH 661.05 Numerical Solution of Differential Equations Fall 2025

Awards

  • CAIMS-Fields Industrial Mathematics Prize, Canadian Applied and Industrial Mathematics Society, Fields Institute. 2025
  • Plenary Speaker, The Third Joint SIAM/CAIMS Annual Meetings, SIAM/CAIMS. 2025

Publications