Patrick Riley is a principal engineer and the senior researcher on the Google
Accelerated Science team. His team collaborates with external scientists to apply
Google's knowledge and experience in machine learning and other computational
approaches to important scientific problems. His work includes applications in drug
discovery, quantum chemistry, materials science, and nuclear fusion. He got his Ph.D.
from Carnegie Mellon University studying artificial intelligence in multi-agent
systems. Before Google Accelerated Science, he spent the first part of his 12 years
at Google in web search, where he developed search features and led a number of
efforts on search logs collection and analysis of user behavior.
Achievement of Sustained Net Plasma Heating in a
Fusion Experiment with the Optometrist Algorithm
E.A. Baltz, E. Trask, M. Binderbauer, M.
Dikovsky, H. Gota, R. Mendoza, J.C. Platt,
Scientific Reports, vol. 7 (2017), pp. 6425
Neural Message Passing for Quantum Chemistry
Justin Gilmer, Samuel S. Schoenholz, Patrick F.
Riley, Oriol Vinyals, George E. Dahl
Prediction errors of molecular machine learning
models lower than hybrid DFT error
Felix Faber, Luke Hutchinson, Huang Bing, Justin Gilmer, Sam Schoenholz, George Dahl, Oriol
Vinyals, Steven Kearnes, Patrick Riley, Anatole von Lilienfeld
Journal of Chemical Theory and Computation (2017)
Molecular graph convolutions: moving beyond
Steven Kearnes, Kevin McCloskey, Marc Berndl, Vijay Pande, Patrick Riley
Journal of Computer-Aided Molecular Design (2016), pp. 1-14
Massively Multitask Networks for Drug Discovery
Bharath Ramsundar, Steven Kearnes,
Patrick Riley, Dale Webster, David Konerding, Vijay Pande
arXiv:1502.02072 [stat.ML] (2015)