01Research page (coming soon)
Scientific machine learning
Model-aware learning methods that respect physical constraints, reveal useful latent structure, and remain dependable beyond the training data.
Mathematics · Scientific discovery · Learning
Mathematics for
data and models.
I am an Associate Professor of Mathematics at Emory University. My research connects scientific machine learning, inverse problems, and numerical linear algebra to make complex systems more understandable and computable.
Matthias “Tia” ChungAssociate Professor
Department of Mathematics
Research initiative
Latent Twins
A new framework for learning compact surrogate models of complex physical systems—pairing representations so inference becomes faster, interpretable, and faithful to the governing science.
Dedicated page coming soonRead the latest paper
Research
Structure, inference, and learning
My group develops computational methods that bring mathematical structure into modern data-driven science.
02Research page (coming soon)
Inverse problems
Fast and robust inference from indirect, incomplete, or noisy observations—with applications in imaging and the physical sciences.
03Research page (coming soon)
Numerical linear algebra
Randomized and structure-exploiting algorithms for large-scale computation, regularization, and uncertainty quantification.
Current highlights
Recent activity
ICERM research visit
Stochastic and Randomized Algorithms in Scientific Computing: Foundations and Applications.
J.T. Oden Faculty Fellowship
Faculty fellowship at the Oden Institute for Computational Engineering and Sciences, UT Austin.
Collaborative research
USDA-supported precision feeding research and an NSF REU in computational mathematics for data science.
Selected publications
Recent work
- 012026
Physics-conforming Latent Twins
Preprint
- 022026
Variational Sparse Paired Autoencoders (vsPAIR) for Inverse Problems and Uncertainty Quantification
Preprint
- 032026
Accelerated reconstruction of 5D free-running MRI with variable projection-augmented Lagrangian (VPAL)
Magnetic Resonance Imaging, 129
- 042025
Latent Twins
Preprint
- 052025
A Paired Autoencoder Framework for Inverse Problems via Bayes Risk Minimization
SIAM Journal on Scientific Computing
- 062025
Sparse L1-Autoencoders for Scientific Data Compression
Journal of Machine Learning for Modeling and Computing, 6(4)
About
Mathematics in conversation with science
Before joining Emory in 2022, I was an Associate Professor at Virginia Tech and an Alexander von Humboldt Fellow at TU Berlin. I received my doctorate in mathematics from the University of Lübeck.
“Seek simplicity, and distrust it.”
Alfred North Whitehead