Peter Frazier

Peter Frazier is the Eleanor and Howard Morgan Professor of Engineering at Cornell University, holding a joint appointment in the School of Operations Research and Information Engineering (ORIE) and serving as a Senior Staff Applied Scientist at Uber. He specializes in sequential decision-making under uncertainty, optimal learning, and Bayesian optimization, with applications in healthcare, e-commerce, and transportation. Frazier earned his B.S. from Caltech (2000) and his M.A. and Ph.D. from Princeton University (2007–2009). His research bridges academia and industry, addressing challenges like Uber’s pricing systems and pandemic response strategies at Cornell. He has received prestigious awards, including the NSF CAREER Award and AFOSR Young Investigator Award, and teaches courses in simulation, optimization, and data science.

• Education: B.S. in Physics/Engineering (Caltech, 2000); M.A./Ph.D. in Operations Research and Financial Engineering (Princeton, 2007–2009).
• Research Focus: Optimal learning methods, Bayesian optimization, sequential decision-making, and their applications in simulation, healthcare, and e-commerce.
• Awards: NSF CAREER Award (2012), AFOSR Young Investigator Award (2010), Best Paper Award at ACM EC (2014).
• Industry Roles: Senior Staff Applied Scientist at Uber (2022–present), leading pricing and data science teams; previously involved in Uber’s surge pricing and Kinetics projects.

His work emphasizes real-world impact, such as designing Cornell’s pandemic response strategy using surveillance testing and contributing to Uber’s pricing algorithms. Frazier’s research also explores applications in materials science, drug discovery, and climate modeling, leveraging Bayesian methods and machine learning.