Collision Course: Artificial Intelligence Meets Fundamental Interactions 

Abstract:  

Modern machine learning has had an outsized impact on many scientific fields, and fundamental physics is no exception.  What is special about fundamental physics, though, is the vast amount of theoretical, experimental, and observational knowledge that we already have about many problems in the field.  Is it possible to teach a machine to “think like a physicist” and thereby advance physics knowledge from the smallest building blocks of nature to the largest structures in the universe?  In this talk, I argue that the answer is “yes”, using the example of particle physics at the Large Hadron Collider to highlight the fascinating synergy between theoretical principles and machine learning architectures.  I also argue that by fusing the “deep learning” revolution with the time-tested strategies of “deep thinking” in physics, we can galvanize research innovation in artificial intelligence more broadly.

Bio: 

Jesse Thaler is the inaugural Director of the NSF AI Institute for Artificial Intelligence and Fundamental Interactions.  He is a theoretical particle physicist who fuses techniques from quantum field theory and machine learning to address outstanding questions in fundamental physics.  His current research is focused on maximizing the discovery potential of the Large Hadron Collider (LHC) through new theoretical frameworks and novel data analysis techniques.  Prof. Thaler is an expert in jets, which are collimated sprays of particles that are copiously produced at the LHC, and he studies the substructure of jets to enhance the search for new phenomena and illuminate the dynamics of gauge theories.  He is also interested in new strategies to probe the nature of dark matter at the LHC and beyond. 

Prof. Thaler joined the MIT Physics Department in 2010, and is currently an Associate Professor in the Center for Theoretical Physics. From 2006 to 2009, he was a fellow at the Miller Institute for Basic Research in Science at the University of California, Berkeley. He received his Ph.D. in Physics from Harvard University in 2006, and his Sc.B. in Math/Physics from Brown University in 2002. He was awarded an Early Career Research Award from the U.S. Department of Energy in 2011, a Presidential Early Career Award for Scientists and Engineers from the White House in 2012, a Sloan Research Fellowship from the Alfred P. Sloan Foundation in 2013, and a Harold E. Edgerton Faculty Achievement Award from MIT in 2016.