AI Advances in Theoretical Physics and Beyond

Abstract:  

AI is now being widely employed for tasks previously considered the domain of theoretical physicists. This talk will explore recent successes of AI in key areas such as identifying symmetries, building new particle physics models, performing symbolic computation, and discovering new data structures and representations. Beyond current AI, the talk will also touch on the future: the rise of quantum computing will establish quantum machine learning as a powerful tool for modeling, optimization, and data analysis. Finally, Large Language Models (LLMs) allow for sophisticated agentic AI to optimize simulation pipelines in particle phenomenology and serve as a true collaborator to human theorists.

Bio:
“Prof. Konstantin Matchev received his undergraduate degree in Physical Engineering in 1990 (Plovdiv University, Bulgaria) and his PhD in theoretical particle physics in 1997 (Johns Hopkins University, advisor Jonathan Bagger). He was a postdoc in the particle theory groups at Fermilab (1997-2000) and CERN (2000-2002) and a faculty member in the Physics Department of the University of Florida (2002-2024). He joined the Department of Physics and Astronomy at the University of Alabama in 2025.
Major awards and distinctions: Department of Energy Outstanding Junior Investigator (2004), University of Florida PhD Advisor/Mentoring Award (2012), Fellow of the American Physical Society (2015), University of Florida Postdoc Mentoring Award (2017), University of Florida Research Foundation Professor (2018-21), University of Florida Term Professor (2018-21), Inaugural Endowed Shelby Distinguished Professor, University of Alabama (2025), Breakthrough Prize in Fundamental Physics (2025).”