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David Duvenaud & Alan Asparu-Guzik; Michael Keiser & Jennifer Wei; David Jones & John Jumper; David Haussler & Alex D'Amour speak on jointly identified challenges.
Author Information
David Haussler (UC Santa Cruz Genomics Institute, University of California, Santa Cruz)
Djork-Arné Clevert (Bayer AG)
Michael Keiser (University of California, San Francisco)
Michael J Keiser PhD is a Chan Zuckerberg Initiative Ben Barres Investigator and an Allen Distinguished Investigator. Michael joined the UCSF faculty as an Assistant Professor in 2014, in the Dept. of Pharmaceutical Chemistry and the Institute for Neurodegenerative Diseases, with appointments in the Dept. of Bioengineering & Therapeutic Sciences and the Bakar Computational Health Sciences Institute. Before this, he co-founded a startup bringing systems pharmacology methods for drug-target prediction to pharma and the US FDA, where they are in use today. He holds multiple degrees from Stanford, including a BSc. in Computer Science. Broadly, the Keiser lab combines machine learning with chemical biology methods to investigate how drug-like small molecules perturb protein networks to achieve their therapeutic effects.
Alan Aspuru-Guzik (University of Toronto)
David Duvenaud (University of Toronto)
David Duvenaud is an assistant professor in computer science at the University of Toronto. His research focuses on continuous-time models, latent-variable models, and deep learning. His postdoc was done at Harvard University, and his Ph.D. at the University of Cambridge. David also co-founded Invenia, an energy forecasting and trading company.
David Jones (University College London)
Jennifer Wei (Google Research)
Alexander D'Amour (Google Brain)
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