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Geoff Pleiss
Student at Franklin W. Olin College of Engineering
Geoff Pleiss is currently an Assistant Professor in the Department of Statistics at the University of British Columbia (UBC), where he is also an inaugural member of the Centre for Artificial Intelligence Decision-Making and Action (CAIDA) and holds the position of Canada CIFAR AI Chair. His research primarily focuses on the intersection of deep learning and probabilistic modeling, particularly concerning uncertainty quantification in machine learning models and its applications in experimental design and scientific discovery.12
Before his current role, Pleiss completed a postdoctoral fellowship at Columbia University and earned his Ph.D. in Computer Science from Cornell University in 2020. He has been involved in significant research and development projects, including co-founding and maintaining the GPyTorch Gaussian process library.23
Pleiss's professional journey also includes experience as a Software Engineer at Pivotal Inc. from 2013 to 2015, where he contributed to software development projects.1 His academic credentials and contributions to the field of machine learning are well-documented, and he has received several honors, including being recognized as a top reviewer for major conferences in the field.12
