In Submission / Under Review
Ask for More Than Bayes Optimal: A Theory of Indecisions for Classification
Mohamad Ndaoud, Peter Radchenko and Bradley Rava
[PDF]

In Submission / Under Review
A Burden Shared is a Burden Halved: A Fairness-Adjusted Approach to Classification
Bradley Rava, Wenguang Sun, Gareth James and Xin Tong
[PDF | R Package]

Journal of the American Statistical Association (to appear)
Asymmetric error control under imperfect supervision: a label-noise-adjusted Neyman-Pearson umbrella algorithm
Shunan Yao, Bradley Rava, Xin Tong and Gareth James
[PDF | JASA]

Journal of the American Statistical Association
Irrational Exuberance: Correcting Bias in Probability Estimates
Gareth James, Peter Radchenko and Bradley Rava
[PDF | JASA | R Package | Python Package]

Conferences / Talks

March 31, 2023
Statistics Department, University of Sydney (Invited Seminar)

March 17, 2023
Monash University EBS (Invited Seminar)

December 17-19, 2022
CMStatistics 2022 (Invited Talk)

October 16-19, 2022
INFORMS 2022 (Invited Talk)

June, 2022
EcoSta 2022. "Advances in statistical learning theory and large-scale inference" - Kyoto, Japan (Invited talk)

June, 2022
Quality and Productivity Research Conference (QPRC 2022) - San Francisco, CA (NSF Travel Grant Award)

April 14, 2022
Fairness in Machine Learning Guest Lecture - Kansas University Business School

Feburary 24, 2022
International Selective Inference Seminar (Invited talk)

Feburary, 2022
Fairness in Machine Learning Guest Lecture - University of Sydney Business School

October 24-27, 2021
INFORMS 2021 (Invited Talk)

August 7-12, 2021
Joint Statistical Meetings 2021 (Invited talk)

July 22, 2020
Google PhD Intern Research Confrence - PIRC

August 1-6, 2020
Joint Statistical Meetings 2020 "Causal Inference, Empirical Bayes and Related Topics in Regression"

June 12, 2020
Google Statistics Journal Club

March 24-27, 2019
ENAR 2019 Spring Meeting - "Classification and variable selection under asymmetric loss" (Invited talk)