Ryan Farell

Biography

Ryan Farell is a PhD candidate in Operations Research and Industrial Engineering at The University of Texas at Austin, where he is affiliated with the Oden Institute’s Computer Visualization Center and the Center for Scientific Machine Learning. He currently serves as Lead Research Scientist on the Dynamic Belief Gamesproject in the UT Computer Science Department under Professor Chandrajit Bajaj, focusing on multi-agent reinforcement learning for adversarial-aware mobile networks. Previously, Ryan contributed to the large-scale DEDRECON initiative, developing real-time deep learning algorithms for multi-modal imaging in wide-area surveillance. Earlier in his graduate work, he was an Equinor Research Fellow, collaborating with Professor Eric Bickel and Equinor’s North America Data Science group to develop machine learning frameworks for subsurface modeling and production forecasting in unconventional reservoirs. His broader research interests lie in scientific machine learning, integrating data-driven approaches with structured physics-based modeling for large-scale optimization, inverse theory, uncertainty quantification, and reinforcement learning, with a special focus on defense and energy applications.

B.S. Statistics, University of Pennsylvania
M.S. Systems Engineering, University of Pennsylvania