\nTo achieve some of the biggest physics discoveries i n the last decade\, including the Higgs boson\, gravitational waves\, and black holes\, physicists had to radically re-imagine the paradigm of working in small teams and instead construct large-scale experiment al collaborations of hundreds or even thousands of scientists. The rec ent success of large-scale AI "foundation models" in various domains b egs the question: could our scientific conventions yet again be restri cting our access to major discoveries? In this talk\, I propose that a multi-disciplinary approach to fundamental physics research will be c ritical to finally answering the grand scientific mysteries about our Universe that have thus far eluded our usual strategies. To achieve th is vision\, AI methods can help us publish detector-agnostic datasets\ , construct richer embeddings of our data\, and highlight connections across varied domains -- but we also need to take care to ensure that we design these tools to uphold our highest priorities as scientists. \n
\nShot Bio: Dr. Mariel Pettee is an interdisciplinary scientist based in Brooklyn\, NY. She is a Chamberlain Postdoctoral Research Fel low at Lawrence Berkeley National Laboratory\, a visiting researcher a t the Flatiron Institute Center for Computational Astrophysics in New York City\, and a member of the ATLAS Experiment at CERN. Her scientif ic research is centered on developing new AI methods to help make disc overies in high-energy particle physics and astrophysics. As a foundin g member of the Polymathic AI collaboration\, she is interested in har nessing multidisciplinary AI foundation models for scientific insight. She received a PhD in Physics from Yale University\, a Masters in Phy sics at the University of Cambridge\, and a Bachelors in Physics & Mat hematics from Harvard University. \n URL:https://www.physics.wisc.edu/events/?id=9096 END:VEVENT END:VCALENDAR