Expanding Boundaries of Molecular Sciences through Machine Learning Approaches

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SCHEDULE

9:30 — 10:00: Reception and Coffee with Pastry

10:00 — 11:20 : Mark Tuckerman, New York University. "Synergizing enhanced sampling and machine learning in molecular simulations for representing and deploying high-dimensional free energy surfaces and discovering reaction coordinates” 

11:30 — 12:50 : Joshua Schrier, Fordham University. "Applications of Machine Learning to Experimental Materials Synthesis: Demonstrated Successes and Limitations”

1:00 — 2:30 : Lunch & Discussion

2:30 — 3:50 : Alexei Kananeka, University of Delaware. "Machine Learning for Quantum Dissipative Dynamics”

4:00 — 5:20: John Terrilla, Queens College, CUNY. "A math perspective on tensor network methods in ML”

5:20 - 6:00: Discussion 

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ORGANIZERS

Seogjoo J. Jang, Department of Chemistry and Biochemistry
Queens College, City University of New York