Dr. Geoff Pleiss

Assistant Professor

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Biography

Geoff Pleiss is an academic researcher with a focus on artificial intelligence and machine learning. He has significant experience exploring Bayesian optimization, probabilistic machine learning, uncertainty quantification, and reliable deep learning. His academic journey includes notable institutions such as Columbia University, where he held a postdoctoral position at the Zuccerman Institute from 2020 to 2023. He completed his Ph.D. in Computer Science at Cornell University in 2020, where he also earned his M.S. in Computer Science in 2018. Prior to his studies at Cornell, he obtained a B.Sc. in Engineering from Olin College of Engineering in 2013. As an associate member in Statistics, he actively engages in interdisciplinary research that combines concepts from statistics and computer science, emphasizing the importance of reliability and quantification of uncertainty in machine learning models.

Research Interests

Requirements for University of British Columbia

Master Program
Requirements
GPA Requirement
Required:3.3
IELTS
Listening
Required:6.5
Reading
Required:6.5
Writing
Required:6.5
Speaking
Required:6.5
Overall
Required:7
TOEFL
Listening
Required:22
Reading
Required:22
Writing
Required:21
Speaking
Required:21
Total
Required:100
Prerequisites
Bachelor's degree in Philosophy or related field 3 credits in formal logic 6 credits at the upper level in history of philosophy 3 credits at the upper level in ethics or value theory 6 credits at the upper level in metaphysics, epistemology, or philosophy of science
Application Checklist
  • Online application form
  • Application fee
  • Transcripts from all post-secondary institutions
  • Three letters of recommendation
  • Writing sample (15-20 pages)
  • Statement of intent
  • Evidence of English language proficiency
Specialization Notes

Offers course-only and thesis routes. Focus areas include philosophy of science, mind, ethics, and Asian philosophy.