Peter I. Frazier
Associate Professor, Cornell University
School of Operations Research
and Information Engineering
Staff Data Scientist, Uber
I work at the intersection between operations research and machine learning.
Half of my time is spent working for Uber as a Staff Data Scientist, and the other half for Cornell as an Associate Professor. I am based in Ithaca, NY.
- [Dec'17] Andrew Wilson and I gave an oral presentation at NIPS on Bayesian Optimization with Gradients, joint work with Jian Wu and Matthias Poloczek.
- [Dec'17] Matthias Poloczek gave a spotlight presentation at NIPS on our joint work with Jialei Wang on Multi-Information Source Optimization.
- [Dec'17] Congrats to Bangrui Chen, who has graduated with his PhD and will join Two Sigma.
- [Jul'17] I am now working at 50% effort for Uber as a Staff Data Scientist while based in Ithaca, and 50% for Cornell as an Associate Professor. This follows a 2-year leave at Uber where I managed data science for uberPOOL, Uber's carpooling product.
- [May'17] Congrats to postdoc Matthias Poloczek, who will be joining University of Arizona as an Assistant Professor.
- [Jan-Aug'17] Congrats to recently graduated PhD students Jialei Wang, Steve Pallone, Weici Hu, and Jian Wu, who will be joining IBM, Uber, Google, and AQR.
- [Jan'16] Congrats to my former PhD student Scott Clark, just named one of
Forbes' 30 under 30 for his Bayesian Optimization startup, SigOpt!
In collaboration with Yelp, we've released
Metrics Optimization Engine (MOE), an open-source service for Bayesian optimal experimental design.
Knowledge Gradient Methods for Bayesian Optimization
- NIPS Bayesian Optimization Workshop, Dec 2017.
- MIT, OR Center, Feb 2016.
Parallel Bayesian Global Optimization of Expensive Functions, for Metrics Optimization at Yelp
- Carnegie Mellon, Machine Learning Department, Feb 2015.
Optimal Learning for Molecular Discovery
- Cornell Center for Applied Math, Oct 2014.
Information Filtering for arXiv.org: Bandits, Exploration vs. Exploitation, and the Cold Start Problem
- Georgia Tech, School of Industrial and Systems Engineering, Apr 2014.
- For others, see the Presentations page. For a complete list, see my CV.
B. Chen, P.I. Frazier,
Dueling Bandits with Weak Regret,
Wu, J., Frazier
The Parallel Knowledge Gradient Method for Batch Bayesian Optimization,
Frazier, D. Kempe, J. Kleinberg, R. Kleinberg,
Economics and Computation, 2014.
A Fully Sequential Elimination Procedure for Indifference-Zone Ranking and Selection with Tight Bounds on Probability of Correct Selection,
Operations Research, 2014.
J. Xie & Frazier,
Sequential Bayes-Optimal Policies for Multiple Comparisons with a Control,
Operations Research, 2013.
Frazier, W.B. Powell & S. Dayanik,
A Knowledge-Gradient Policy for Sequential Information Collection,
SIAM Journal on Control and Optimization, 2008.
- For a full list see the
or my CV.