Collision Course: Particle Physics Meets Machine Learning
- Speaker
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Jesse Thaler, Ph.D.Professor of Physics, Massachusetts Institute of Technology
Director, NSF Institute for Artificial Intelligence and Fundamental Interactions
The 2024 lecture series in mathematics and computer science is “Machine Learning in the Natural Sciences.” Machine learning has become a transformative tool for advancing science. In these lectures, scientists will discuss their use of machine learning in everything from biology and oceanography to astrophysics and particle physics. These applications are sparking discoveries while also helping scientists uncover what the tools are actually gleaning from data.
2024 Lecture Series Themes
Mathematics and Computer Science: Machine Learning in the Natural Sciences
Presidential Lectures are free public colloquia centered on four main themes: Biology, Physics, Mathematics and Computer Science, and Neuroscience and Autism Science. These curated, high-level scientific talks feature leading scientists and mathematicians and are intended to foster discourse and drive discovery among the broader NYC-area research community. We invite those interested in the topic to join us for this weekly lecture series.
Modern machine learning has had an outsized impact on many scientific fields, and particle physics is no exception. What is special about particle physics, though, is the vast amount of theoretical knowledge we already have about many problems in the field and the daunting deluge of data coming from flagship experiments like the Large Hadron Collider.
In this Presidential Lecture, Jesse Thaler will explain how one can teach a machine to “think like a physicist” by embedding theoretical principles into advanced machine learning architectures. At the same time, Thaler will advocate that physicists must learn how to “think like a machine” by capitalizing on advances in computational optimization to perform precision calculations and identify potential signals of new physics.
About the Speaker
Thaler 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 through new theoretical frameworks and novel data analysis techniques. Thaler joined the MIT Physics Department in 2010 and is currently a professor at the university’s Center for Theoretical Physics. In 2020, he became the inaugural director of the NSF Institute for Artificial Intelligence and Fundamental Interactions.