Zixiang Tong

Department of Aerospace Engineering

and Engineering Mechanics

The University of Texas at Austin

My research focuses on advancing Digital Image/Volume Correlation (DIC/DVC) under extremely challenging conditions — complex geometry, large deformation, and biological tissues. I combine Machine Learning and Computer Vision to build open-source tools that make high-accuracy deformation measurement accessible to the experimental mechanics community.

Research Interests:

Digital Image Correlation (DIC) & Digital Volume Correlation (DVC)
Deep Learning for Displacement Estimation
Fracture Mechanics + DIC
Soft Material & Biomechanical Characterization
Stereo Vision & 3D Measurement Systems
Finite Element Simulation (Abaqus, COMSOL Multiphysics)

news

Jun 01, 2026	Will present RAFTcorr: An Open-Source, Deep Learning DIC Framework for Dense Displacement Measurement at SEM Annual 2026 in Norfolk, VA.
Mar 01, 2026	Honored to contribute to the iDICs Good Practices Guide (Edition 2). Thank you to the entire GPG team and especially my advisor, Prof. Jin Yang, for the guidance and opportunity.
Feb 20, 2026	Attended the 60th Texas Society for Microscopy Annual Meeting with lab members, featuring oral presentations and hands-on tutorials on super-resolution confocal microscopy and TEM.
Jan 15, 2026	Our paper Machine Learning-Aided Spatial Adaptation for Improved DIC Analysis of Complex Geometries has been published in Strain.
Jan 15, 2026	Shared research experiences at a panel discussion at the Texas Material Scientists and Engineers (TMSE) meeting with Dylan Baird.

selected publications

Strain

ML-Aided Spatial Adaptation

Jeffrey Leu, Zixiang Tong, Andrew Doty, and 2 more authors

Strain, 2026

DOI Bib HTML Code

@article{leu2026mlaided,
  title = {ML-Aided Spatial Adaptation},
  author = {Leu, Jeffrey and Tong, Zixiang and Doty, Andrew and Tsimpoukis, Solon and Yang, Jin},
  journal = {Strain},
  volume = {62},
  number = {1},
  pages = {e70022},
  year = {2026},
  doi = {10.1111/str.70022},
}

Exp Mech

3D Stereo Adaptive Mesh Augmented Lagrangian Digital Image Correlation

Zixiang Tong, Dan Frolkin, Hongyang Shi, and 5 more authors

Experimental Mechanics, 2025

DOI Bib HTML Code

@article{tong2025stereoaldic,
  title = {3D Stereo Adaptive Mesh Augmented Lagrangian Digital Image Correlation},
  author = {Tong, Zixiang and Frolkin, Dan and Shi, Hongyang and LaRue, Trace and Rausch, Manuel K. and Zhang, Yujie and Knight, Virginia and Yang, Jin},
  journal = {Experimental Mechanics},
  volume = {65},
  pages = {1387--1411},
  year = {2025},
  doi = {10.1007/s11340-025-01225-7},
}

Measurement

Refraction Error Analysis in Stereo Vision for System Parameters Optimization

Zixiang Tong, Liuning Gu, and Xinxing Shao

Measurement, 2023

DOI Bib HTML

@article{tong2023refraction,
  title = {Refraction Error Analysis in Stereo Vision for System Parameters Optimization},
  author = {Tong, Zixiang and Gu, Liuning and Shao, Xinxing},
  journal = {Measurement},
  volume = {222},
  pages = {113650},
  year = {2023},
  doi = {10.1016/j.measurement.2023.113650},
}

TAML

Optimization of the Forearm Angle for Arm Wrestling Using Multi-camera Stereo Digital Image Correlation: A Preliminary Study

Zixiang Tong, Xinxing Shao, Zhenning Chen, and 1 more author

Theoretical and Applied Mechanics Letters, 2021

DOI Bib HTML

@article{tong2021armwrestling,
  title = {Optimization of the Forearm Angle for Arm Wrestling Using Multi-camera Stereo Digital Image Correlation: A Preliminary Study},
  author = {Tong, Zixiang and Shao, Xinxing and Chen, Zhenning and He, Xiaoyuan},
  journal = {Theoretical and Applied Mechanics Letters},
  volume = {11},
  number = {6},
  pages = {100287},
  year = {2021},
  doi = {10.1016/j.taml.2021.100287},
}

Under Review

RAFTcorr: An Open-Source, Deep Learning Digital Image Correlation Framework for Dense Displacement Measurement

Zixiang Tong, Lehu Bu, Qihang Shi, and 2 more authors

2025

Bib Code

@article{tong2025raftcorr,
  title = {RAFTcorr: An Open-Source, Deep Learning Digital Image Correlation Framework for Dense Displacement Measurement},
  author = {Tong, Zixiang and Bu, Lehu and Shi, Qihang and Du, Runtian and Yang, Jin},
  year = {2025},
}