World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
6917
World Ranking
11105
National Ranking
4613

Overview

Peter I. Frazier is affiliated with Cornell University in the United States. Their research primarily centers on computer science, with a focus on artificial intelligence, management science, and operations research. They also engage in studies related to infectious diseases, computational theory, mathematics, and molecular biology.

Their work covers several main topics including advanced multi-objective optimization algorithms, advanced bandit algorithms research, SARS-CoV-2 and COVID-19 research, machine learning and algorithms, Gaussian processes and Bayesian inference, machine learning and data classification, as well as transportation and mobility innovations.

Frequent coauthors of Peter I. Frazier include Raul Astudillo, Jiayue Wan, Shane G. Henderson, Yujia Zhang, and David B. Shmoys.

Their publications are often found in venues such as arXiv (Cornell University), SSRN Electronic Journal, bioRxiv (Cold Spring Harbor Laboratory), Operations Research, and Proceedings of the National Academy of Sciences.

Recent papers include:

  • Parallel Bayesian Global Optimization of Expensive Functions, 2020, Operations Research
  • Modeling for COVID-19 college reopening decisions: Cornell, a case study, 2021, Proceedings of the National Academy of Sciences
  • Tuning Materials-Binding Peptide Sequences toward Gold- and Silver-Binding Selectivity with Bayesian Optimization, 2021, ACS Nano
  • Bayesian Optimization with Expensive Integrands, 2022, SIAM Journal on Optimization
  • Multi-information source Bayesian optimization of culture media for cellular agriculture, 2022, Biotechnology and Bioengineering

Best Publications

  • A Tutorial on Bayesian Optimization

    Peter I. Frazier

  • A Knowledge-Gradient Policy for Sequential Information Collection

    Peter I. Frazier;Warren B. Powell;Savas Dayanik

  • The Knowledge-Gradient Policy for Correlated Normal Beliefs

    Peter Frazier;Warren Buckler Powell;Savas Dayanik

  • Distance Dependent Chinese Restaurant Processes

    David M. Blei;Peter I. Frazier

  • The Correlated Knowledge Gradient for Simulation Optimization of Continuous Parameters using Gaussian Process Regression

    Warren Scott;Peter Frazier;Warren Buckler Powell

  • Bayesian Optimization for Materials Design

    Peter I. Frazier;Jialei Wang

  • The Knowledge Gradient Algorithm for a General Class of Online Learning Problems

    Ilya O. Ryzhov;Warren B. Powell;Peter I. Frazier

  • ALE: a generic assembly likelihood evaluation framework for assessing the accuracy of genome and metagenome assemblies

    Scott C. Clark;Rob Egan;Peter I. Frazier;Zhong Wang

  • The Parallel Knowledge Gradient Method for Batch Bayesian Optimization

    Jian Wu;Peter I. Frazier

  • The Knowledge-Gradient Algorithm for Sequencing Experiments in Drug Discovery

    Diana M. Negoescu;Peter I. Frazier;Warren B. Powell

  • Bayesian Optimization with Gradients

    Jian Wu;Matthias Poloczek;Andrew Gordon Wilson;Peter I. Frazier

  • Multi-Information Source Optimization

    Matthias Poloczek;Jialei Wang;Peter I. Frazier

  • Parallel Bayesian Global Optimization of Expensive Functions

    Jialei Wang;Scott C. Clark;Eric Liu;Peter I. Frazier

  • Sequential Hypothesis Testing under Stochastic Deadlines

    Peter Frazier;Angela J Yu

  • Predicting Bike Usage for New York City's Bike Sharing System

    Divya Singhvi;Somya Singhvi;Peter I. Frazier;Shane G. Henderson

  • Incentivizing exploration

    Peter Frazier;David Kempe;Jon Kleinberg;Robert Kleinberg

  • Sequential Sampling with Economics of Selection Procedures

    Stephen E. Chick;Peter Frazier

  • Efficient search of compositional space for hybrid organic-inorganic perovskites via Bayesian optimization

    Henry C. Herbol;Weici Hu;Peter Frazier;Paulette Clancy

  • TWENTY QUESTIONS WITH NOISE: BAYES OPTIMAL POLICIES FOR ENTROPY LOSS

    Bruno Jedynak;Peter I. Frazier;Raphael Sznitman

  • Hierarchical Knowledge Gradient for Sequential Sampling

    Martijn R.K. Mes;Warren B. Powell;Peter I. Frazier

  • Practical multi-fidelity bayesian optimization for hyperparameter tuning supplementary material

    Jian Wu;Saul Toscano-Palmerin;Peter I. Frazier;Andrew Gordon Wilson

Frequent Co-Authors

Warren B. Powell
Warren B. Powell Princeton University
Shane G. Henderson
Shane G. Henderson Cornell University
Andrew Gordon Wilson
Andrew Gordon Wilson New York University
David M. Blei
David M. Blei Columbia University
Thorsten Joachims
Thorsten Joachims Cornell University
Claire Cardie
Claire Cardie Cornell University
Jeffrey A. Toretsky
Jeffrey A. Toretsky Georgetown University
Samuel J. Gershman
Samuel J. Gershman Harvard University
Nathan C. Gianneschi
Nathan C. Gianneschi Northwestern University

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