Aaron Dinner (UChicago): AI+ Science Schmidt Fellows Speaker Series

Organized by the University of Chicago’s Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship Program.

Agenda
4:00pm – 4:45pm:  Presentation
4:45pm – 5:00pm:  Q&A
5:00pm – 5:30pm: Reception

Meeting location
William Eckhardt Research Center. Room 401
5640 S Ellis Avenue, Chicago, IL 60637
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Abstract: Accurate quantitative predictions concerning reactions in molecular systems are fundamental to chemistry and are of practical importance for designing the next generations of catalysts, materials for sustainable energy, therapeutics, and molecular sensors, to name just a few examples. Traditional kinetic theories assume a well-defined activated complex (transition state) and a simple form for the underlying (free) energy landscape governing the dynamics. However, reactions in complex systems typically studied today involve many intermediates and competing pathways. New computational methods are needed to describe such dynamics. I will discuss how machine learning can be leveraged to elucidate reaction mechanisms and their kinetics from time series data and show examples from my group’s work on proteins.

Bio: Aaron Dinner is a Professor of Chemistry and Deputy Dean of the Physical Sciences Division at the University of Chicago. He obtained his A.B. in Biochemical Sciences in 1994 and his Ph.D. in Biophysics in 1999, both from Harvard University. Following postdoctoral research at Oxford University from 1999 to 2001 and University of California, Berkeley from 2001 to 2003, he joined the faculty at the University of Chicago in 2003. From 2012 to 2018, he served as the Director of the James Franck Institute, a longstanding interdisciplinary institute bringing together research in condensed matter physics; atomic, molecular, and optical (AMO) physics; biophysics; and physical chemistry. His research seeks to understand how the complex behaviors of living systems arise from molecular interactions. To this end, he and his group have developed and deployed simulation and machine learning algorithms for characterizing rare events, with a focus on molecular transitions. They have also worked closely with experimentalists to analyze biological measurements and formulate models of processes that enable self-organization in space and time, including cell-fate choices during development and activation of the immune system, timing of the bacterial cell cycle, circadian rhythms, and cytoskeletal dynamics. His honors include a Searle Scholarship, National Science Foundation CAREER Award, Sloan Fellowship, and an American Physical Society Fellowship.

Parking
Campus North Parking
5505 S Ellis Ave
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