Geoff Pleiss

Geoff Pleiss is an assistant professor in the Department of Statistics at the University of British Columbia, as well as a Canada CIFAR AI Chair affiliated with the Vector Institute. He earned a Ph.D. in Computer Science from Cornell University under the supervision of Prof. Kilian Weinberger. Geoff’s research group specializes in uncertainty quantification in machine learning, especially within the contexts of Bayesian optimization, spatiotemporal modelling, and scientific discovery. Additionally, he has co-founded many widely-used open source software projects, including the GPyTorch, LinearOperator, and CoLA libraries.