PeopleofSuperintelligence

Researcher

Geoff Pleiss

Geoff Pleiss is a machine learning researcher whose work links neural network calibration with Gaussian process inference. He earned an engineering degree at Olin and a computer science Ph.D. at Cornell, then coauthored work on calibrated neural networks and scalable Gaussian processes. From 2020 to 2023, he worked at Columbia with John Cunningham. As of October 2026, he is an assistant professor at UBC, a Canada CIFAR AI Chair, and a Vector Institute faculty member. He received the 2025 Blackwell-Rosenbluth Award, and a paper with his students won AISTATS’s 2026 Best Student Paper Award.

Timeline

  1. 2009–2013

    Engineering at Olin

    He earns a B.Sc. in engineering at Olin College of Engineering in 2013.

  2. 2015–2020

    Cornell computer science degrees

    At Cornell, he studies computer science from 2015 to 2020. There, he earns an M.S. in computer science in 2018 and completes a Ph.D. in 2020 under Kilian Weinberger.

  3. 2017

    Calibrating neural networks

    In 2017, he coauthors the ICML paper “On Calibration of Modern Neural Networks.” It presents temperature scaling as a simple method that can nearly restore network calibration.

  4. 2018

    GPyTorch and LOVE

    In 2018, he coauthors the GPyTorch paper, a PyTorch library for scalable Gaussian process inference; its BBMM method reduces exact inference’s asymptotic complexity from O(n³) to O(n²). He also coauthors LOVE, which uses Lanczos to approximate predictive covariance; in experiments, it computes covariances up to 2,000 times faster and draws samples 18,000 times faster than existing methods. He co-founds GPyTorch.

  5. 2020–2023

    Postdoctoral work at Columbia

    From 2020 to 2023, he works as a postdoctoral researcher at Columbia University, hosted by John Cunningham, with affiliations in the Department of Statistics and Zuckerman Institute.

  6. 2025

    The Blackwell-Rosenbluth Award

    In 2025, he receives the Blackwell-Rosenbluth Award, which recognizes outstanding junior Bayesian research.

  7. 2026

    An AISTATS paper award

    In 2026, he and his students receive the AISTATS Best Student Paper Award for “We Still Don’t Understand High-Dimensional Bayesian Optimization.”

  8. As of October 2026

    Assistant professor at UBC

    As of October 2026, he is an assistant professor in UBC’s Department of Statistics, a Canada CIFAR AI Chair, and a Vector Institute faculty member.

Career

  1. NowUniversity of British ColumbiaAssistant Professor
  2. NowVector InstituteFaculty Member
  3. 2020–2023Columbia UniversityPostdoctoral Researcher

Education

  1. 2020Cornell UniversityPhD in Computer Science
  2. 2013Olin College of EngineeringB.Sc. in Engineering

From the biography.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Geoff Pleiss. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  2. The median h-index is 48 at universities and 14 at frontier AI labsIncludes University of British Columbia. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  3. Of 943 people shaping AI who worked at Google, 446 work there nowIncludes Vector Institute. Our estimates of where the 943 people shaping AI who worked at Google and Google DeepMind work now: 446 at Google and 452 across 278 other organizations.
  4. Nonprofit roles are 2.3 times as common in AI safetyIncludes Vector Institute. We estimate where people focused on safety, alignment and evaluation work. Nonprofit roles appear for 25.1% of safety people with known affiliations, compared with 11.0% in other areas.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Geoff Pleiss yet. Send us a free-licensed photo.

  1. Geoff Pleiss | Computer Science at UBC cs.ubc.ca. Checked 22 October 2026.
  2. Geoff Pleiss - Vector Institute for Artificial Intelligence vectorinstitute.ai. Checked 22 October 2026.
  3. On Calibration of Modern Neural Networks proceedings.mlr.press. Checked 22 October 2026.
  4. Calibrating Neural Networks geoffpleiss.com. Checked 22 October 2026.
  5. GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration arxiv.org. Checked 22 October 2026.
  6. GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration | NeurIPS Proceedings proceedings.neurips.cc. Checked 22 October 2026.
  7. GPyTorch github.com. Checked 22 October 2026.
  8. Constant-Time Predictive Distributions for Gaussian Processes arxiv.org. Checked 22 October 2026.
  9. Constant-Time Predictive Distributions for Gaussian Processes | PMLR proceedings.mlr.press. Checked 22 October 2026.
  10. Seminar: Bridging the Gap Between Deep Learning and Probabilistic Modeling | Computer Science | Virginia Tech website.cs.vt.edu. Checked 22 October 2026.
  11. Geoff Pleiss Awarded the 2025 Blackwell-Rosenbluth Award | UBC Statistics stat.ubc.ca. Checked 22 October 2026.
  12. Geoff Pleiss Awarded AISTATS 2026 Best Student Paper Award | UBC Statistics stat.ubc.ca. Checked 22 October 2026.
  13. Geoff Pleiss geoffpleiss.com. Checked 22 October 2026.