Matt Repasky

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About Me

I am a third-year Machine Learning Ph.D. student at the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. I am fortunate to be advised by Dr. Yao Xie. My interests are at the intersection of high-dimensional statistics, generative modeling, and reinforcement learning. My most recent work focuses on developing an optimization strategy to compute the Stein discrepancy for statistical hypothesis testing in high-dimensional spaces. I focus on applications to the natural sciences, including planetary science, energy systems, and materials. My research in collaboration with Dr. Xie is also focused on: developing methods to detect corrosion in coated materials to reduce the environmental impact of the coating industry, studying fair and efficient patrol and dispatch strategies using RL, and physically characterizing and denoising high-dimensional scanning probe microscopy data.

In May 2021, I earned a BS in Physics with a concentration in Astrophysics from Georgia Tech. Working in the Computational Cosmology Group run by Dr. John Wise as an undergraduate student, I managed and analyzed cosmological simulations of stellar clusters in the early universe run on supercomputers at Georgia Tech PACE and the Texas Advanced Computing Center (TACC).

Other Info

• In Summer 2023, I was an intern at NASA Goddard Space Flight Center, where I was advised by Dr. Erwan Mazarico.
• In Summer 2022, I was a technical research aide intern at Argonne National Laboratory, where I was advised by Dr. Feng Qiu.
• In Spring 2022, I was a graduate teaching assistant/tutor for Regression and Forecasting (ISYE 4031) at Georgia Tech.
• In Fall 2021, I was a graduate teaching assistant/tutor for Probability with Applications (ISYE 2027) at Georgia Tech.
• In Spring 2021, I was a recipient of a President’s Undergraduate Research Award (PURA) at Georgia Tech for my undergraduate research with Dr. Xie.