Matt Hyatt

Ph.D. Student

Matt Hyatt is a Ph.D. student in Computer Science at Loyola University Chicago and a DoD NDSEG Fellow. His research focuses on robot learning, humanoid robots, multi-embodiment learning, and machine learning for scientific applications. His work includes robot learning for the automation of chemistry laboratories, robot policy online self-improvement, and the use of high-performance computing for machine learning and scientific research. He has conducted research at Loyola University Chicago, Argonne National Laboratory, Argonne Leadership Computing Facility, and the University of Texas at Austin.

Major

Education

Ph.D. in Computer Science, Loyola University Chicago — 2024–In Progress
B.S. in Computer Science, Loyola University Chicago — 2020–2024

Research Interests

Robot Learning, Humanoid Robotics, Multi-Embodiment Learning, Machine Learning, Deep Learning, High-Performance Computing, Scientific Machine Learning, Autonomous Laboratory Automation

Professional Employment

Graduate Research Assistant, Argonne Leadership Computing Facility — 2025–Present
Graduate Research Assistant, Loyola University Chicago — 2024–Present
Visiting Researcher, University of Texas at Austin — 2024
Research Assistant, Argonne National Laboratory — 2023
Data Science Intern, Beam Suntory — 2023
Research Assistant (NSF REU), Purdue University — 2022
Research Assistant, Loyola University Chicago — 2021–2024