Geoff Pleiss headshot

Geoff Pleiss

Faculty Member

Assistant Professor, Department of Statistics, University of British Columbia

Canada CIFAR Artificial Intelligence Chair

Geoff Pleiss is an assistant professor in the Department of Statistics at the University of British Columbia. Additionally, he holds a faculty position at the Vector Institute. Geoff earned his Ph.D. in Computer Science from Cornell University in 2020, where he was supervised by Kilian Weinberger. Following his doctoral studies, he worked with John Cunningham at the Zuckerman Institute of Columbia University. Geoff’s research interests encompass a wide range of topics in machine learning, including reliable neural networks, uncertainty quantification, probabilistic modeling, and Bayesian optimization. He is also an avid open source contributor, having co-founded the GPyTorch, LinearOperator, and CoLA software libraries.

Research Interests

  • Neural Networks
  • Uncertainty Quantification
  • Bayesian Optimization
  • Probabilistic Modeling