Zifeng Zhao
Associate Professor
IT, Analytics, and Operations
574-631-5065
357 Mendoza College of Business
- Biography
- Background
- Publications
- Books
- Grants
Zifeng Zhao is an Assistant Professor of Business Analytics at the Mendoza College of Business. His research focuses on solving business analytics problems via statistics and machine learning. His interests include change-point analysis, online learning, copula-based dependence modeling and extreme value theory. His research has been applied to areas like revenue management, portfolio optimization, insurance risk classification and pricing. Zhao has a PhD in Statistics and an MS degree in Machine Learning from the University of Wisconsin-Madison, and a BS degree in Financial Risk Management from the Chinese University of Hong Kong.
Education
Ph D, University of Wisconsin - Madison
MS, University of Wisconsin - Madison
BS, Chinese University of Hong Kong
Areas of Expertise
Change Point Detection
Revenue Management and Learning
Copula and Dependence
Extreme Value Theory
Editorial Boards
Associate Editor
Journal of Business & Economic Statistics
July 1, 2025
Journal of Business & Economic Statistics
July 1, 2025
"Discrete choice models with piecewise linear utility: modeling, estimation and pricing", (With Chenxu Ke, Ruxian Wang), Manufacturing & Service Operations Management - Accepted (awaiting publication)
"Contextual dynamic pricing: algorithms, optimality, and local differential privacy constraints", (With Feiyu Jiang, Yi Yu), Journal of the American Statistical Association - Accepted (awaiting publication)
"High-dimensional dynamic pricing under non-stationarity: learning and earning with change-point detection", (With Feiyu Jiang, Yi Yu, Xi Chen), Management Science - Accepted (awaiting publication)
"Learning personalized ad impact via contextual reinforcement learning under delayed rewards", (With Yuwei Cheng, Haifeng Xu), Neural Information Processing Systems (Neurips) 2025
"Transfer learning for nonparametric contextual dynamic pricing", (With Fan Wang, Feiyu Jiang, Yi Yu), International Conference on Machine Learning (ICML) 2025
"SNSeg: An R package for time series segmentation via self-normalization", (With Shubo Sun, Feiyu Jiang, Xiaofeng Shao), The R Journal
"Change-point inference in high-dimensional regression models under temporal dependence", (With Haotian Xu, Daren Wang, Yi Yu), Annals of Statistics, 52, 2024
"Anticipated Wait and Its Effects on Consumer Choice, Pricing, and Assortment Management", (With Ruxian Wang, Chenxu Ke), Manufacturing & Service Operations Management, 2024
"Enhanced Pricing and Management of Bundled Insurance Risks with Dependence-Aware Prediction using Pair Copula Construction", (With Peng Shi), Journal of Econometrics, 2024
"A Composite Likelihood-Based Approach for Change-Point Detection in Spatio-Temporal Processes", (With Ting Fung Ma, Wai Leong Ng, Chun Yip Yau), Journal of the American Statistical Association, 2024
"Risk analysis via generalized Pareto distributions", (With Yi He, Liang Peng, Dabao Zhang), Journal of Business & Economic Statistics, 40, 2022
"Modeling multivariate time series with copula-linked univariate D-vines", (With Peng Shi, Zhengjun Zhang), Journal of Business & Economic Statistics, 40, 2022
"Modelling the COVID-19 infection trajectory: A piecewise linear quantile trend model", (With Feiyu Jiang, Xiaofeng Shao), Journal of the Royal Statistical Society - Series B, 84, 2022
"Change-point detection for sparse and dense functional data in general dimensions", (With Carlos Padilla, Daren Wang, Yi Yu), Advances in Neural Information Processing Systems
"Segmenting time series via self-normalization", (With Feiyu Jiang, Xiaofeng Shao), Journal of the Royal Statistical Society: Series B
"Functional Linear Regression with Mixed Predictors", (With Daren Wang, Yi Yu, Rebecca Willet), Journal of Machine Learning Research, 2022
"Knowledge Learning of Insurance Risks Using Dependence Models", (With Shi Peng, Xiaoping Feng), INFORMS Journal on Computing, 2021
"Statistically and computationally efficient change point localization in regression settings", (With Daren Wang, Kevin Lin, Rebecca Willet), Journal of Machine Learning Research, 22, 2021
"Alternating dynamic programming for multiple epidemic change-point estimation", (With Chun Yip Yau), Journal of Computational and Graphical Statistics, 30
"Regression for copula-linked compound distributions with applications in modeling aggregate insurance claims", (With Peng Shi), Annals of Applied Statistics, 14, 2020
"Dynamic bivariate Peak over Threshold model for joint tail risk dynamics of financial markets", Journal of Business & Economic Statistics, 39
"Modeling maxima with autoregressive conditional Fréchet model", (With Zhengjun Zhang, Rong Chen), Journal of Econometrics, 2018
"Semiparametric dynamic max-copula model for multivariate time series", (With Zhengjun Zhang), Journal of the Royal Statistical Society - Series B, 2018
"Inference for multiple change-points in time series via likelihood ratio scan statistics", (With Chunyip Yau), Journal of the Royal Statistical Society - Series B, 78, 2016
"Regressor and disturbance have moments of all order, least squares estimator has none", (With Kenneth West), Statistics & Probability Letters, 115, 2016
"Adjusting for bias in long horizon regressions using R", (With Kenneth West), Handbook of Statistics, 41, 2019
Collaborative Research: Segmentation of Time Series via Self-normalization, NSF, $100,000
Prescriptive Analytics for Multiple-choice Models in Hotel Bookings and Upgrades, Oracle Labs, $30,000