All times in this Schedule are Pacific Time (PT)
Monday, October 30, 2017
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9:00 - 9:40
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10:15 - 10:55
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Gabor Csanyi (University of Cambridge)
How do we build good databases for machine learning of force fields?
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11:30 - 12:10
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2:30 - 3:10
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4:00 - 4:40
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Imre Risi Kondor (University of Chicago)
Covariant neural networks for learning graphs and atomic potentials
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Tuesday, October 31, 2017
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9:00 - 9:40
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10:15 - 10:55
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11:30 - 12:10
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2:30 - 3:10
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Wednesday, November 1, 2017
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9:00 - 9:40
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10:15 - 10:55
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11:30 - 12:10
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2:30 - 3:10
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4:00 - 4:40
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David Bindel (Cornell University)
Scalable algorithms for kernel-based surrogates in prediction and optimization

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Thursday, November 2, 2017
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9:00 - 9:40
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Mark Tuckerman (New York University)
Exploration and learning of energy and free energy landscapes
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10:15 - 10:55
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Steve Brunton (University of Washington)
Data-driven characterization and control of complex systems

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11:30 - 12:10
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Olexandr Isayev (University of North Carolina)
Towards Universal ML Potential for Organic Molecules
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2:30 - 3:10
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Gus Hart (Brigham Young University)
Extending the SOAP descriptor to make alloy GAP potentials
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4:00 - 4:40
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Gareth Conduit (University of Cambridge)
Who needs atoms to design materials?
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Friday, November 3, 2017
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9:00 - 9:40
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10:15 - 10:55
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Cecilia Clementi (Rice University)
Incorporating Experimental Data in Long Timescales Macromolecular Simulations
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11:30 - 12:10
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Thomas Miller (California Institute of Technology)
Development of a coarse-grained model for co-translational membrane protein folding
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2:30 - 3:10
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