LANS Seminar

Seminar Title: A Projected Reality: Data-Driven and Model Aware

Speaker: Matthias Chung, Associate Professor of Mathematics, Emory University

Date: Monday, July 21, 2025

Time: 2:00 PM-3:00 PM (In-Person)

Location: Hybrid, Bldg. 240, Conference Room 1501

Description: Inverse problems are everywhere—from imaging and geophysics to medicine and engineering—but solving them often means wrestling with expensive models and elusive uncertainties. In this talk, we explore a new perspective: using paired autoencoders to learn the structure of inverse problems directly from data. This approach bypasses the need for forward model evaluations during inference, offering a powerful, flexible, and fast alternative to traditional methods. By jointly learning compact representations of both data and solutions, we unlock new possibilities for robust estimation, real-time applications, and generalization across problem domains. This is a step toward rethinking how we solve inverse problems in the era of machine learning.

Bio: Matthias Chung is an Associate Professor of Mathematics at Emory University. His research focuses on scientific machine learning, inverse problems, numerical analysis, and uncertainty quantification, with applications in biomedical imaging, geosciences, and computational biology. He has published extensively on sparse representations, autoencoders, and optimization methods for large-scale inverse problems. Dr. Chung previously held faculty positions at Virginia Tech and Texas State University and is a recipient of the Alexander von Humboldt Fellowship. He is actively engaged in the scientific community through organizing international workshops and summer schools, and currently leads multiple NSF-funded research and education initiatives.

Please note that the meeting URL for this event can be seen on the cels-seminars website which requires an Argonne login.