Research Interests
Methodology:
Data-Driven Algorithms, Online Learning Algorithms, Approximation Algorithms, Stochastic Modeling and Optimization.
Application:
Pricing and Revenue Management, Inventory Management, Supply Chain Management, Service Operations.
Employment
University of Colorado Boulder
Leeds School of Business
Assistant Professor - June 2020 - Now
Pennsylvania State University
Harold and Inge Marcus Department of Industrial and Manufacturing Engineering
Assistant Professor - August 2017-May 2020
Education:
Ph.D. in Industrial & Operations Engineering
Sep 2012-August 2017
University of Michigan, Ann Arbor, MI, USA
Advisors: Prof. Xiuli Chao and Prof. Cong Shi
Thesis title: Data-Driven Algorithms for Stochastic Supply Chain Systems: Approximation and Online Learning
Sep 2008-May 2012
The Chinese University of Hong Kong, Hong Kong, China
First-Class Honours
JOURNAL PUBLICATION and PrEPRINT
An Efficient Learning Framework for Multi-Product Inventory Systems with Customer Choices [DOI]
Xiangyu Gao and Huanan Zhang
Under Major revision at Production and Operations Management
Online Learning and Optimization for Revenue Management Problems with Add-on Discounts [DOI]
David Simchi-Levi, Rui Sun, and Huanan Zhang (alphabetically ordered)
Under second round Major revision at Management Science.
Joint Learning and Optimization for Multi-product Pricing (and Ranking) under a General Cascade Click Model [DOI]
Xiangyu Gao, Stefanus Jasin, Sajjad Najafi, and Huanan Zhang (alphabetically ordered)
R&R at Management Science.
Finalist of POMS-JD.com 2019 Best Data-Driven Research Paper Competition.
Online Learning and Optimization of (Some) Cyclic Pricing Policies in the Presence of Patient Customers [DOI]
Huanan Zhang and Stefanus Jasin
Accepted at Manufacturing & Service Operations Management.
Closing the Gaps: An Online Learning Algorithm for Lost-sales Inventory Systems with Lead Times [DOI]
Huanan Zhang, Xiuli Chao, and Cong Shi
Management Science, Vol. 66(5), 1962-1980, 2020.
Perishable Inventory Problems: Convexity Results for Base-Stock Policies and Learning Algorithms under Censored Demand [DOI]
Huanan Zhang, Xiuli Chao, and Cong Shi
Operations Research, Vol. 66(5), 1189-1456, 2018.
Approximation Algorithms for Capacitated Perishable Inventory Systems with Positive Lead Times [DOI]
Xiuli Chao, Xiting Gong, Cong Shi, Chaolin Yang, Huanan Zhang, and Sean X. Zhou (alphabetically ordered)
Management Science, Vol. 64(11), 5038-5061, 2018.
Stochastic Regret Minimization for Revenue Management Problems with Nonstationary Demands [DOI]
Huanan Zhang, Cong Shi, Chao Qin, and Cheng Hua
Naval Research Logistics, Vol. 63(6), 433-448, 2016.
Approximation Algorithms for Perishable Inventory Systems with Setup Cost [DOI]
Huanan Zhang, Cong Shi, and Xiuli Chao
Operations Research, Vol. 64(2), pp. 432-440, 2016.
Approximation Algorithms for Perishable Inventory Systems [DOI]
Xiuli Chao, Xiting Gong, Cong Shi, and Huanan Zhang (alphabetically ordered)
Operations Research, Vol. 63, no. 3, pp. 585-601, 2015.
A Faster Algorithm for the Resource Allocation Problem with Convex Cost Functions [DOI]
Cong Shi, Huanan Zhang, and Chao Qin
Journal of Discrete Algorithms, Vol. 34, pp. 137-146, 2015.
Approximation Algorithms for Capacitated Stochastic Inventory Systems with Setup Costs [DOI]
Cong Shi, Huanan Zhang, Xiuli Chao, and Retsef Levi
Naval Research Logistics, Vol. 61, no. 4, pp. 304-319, 2014.
Selected Working Papers
Authors underlined are Ph.D. supervisees.
Assortment Optimization with Multi-Item Basket Purchase under Multivariate MNL Model [DOI]
Chengyi Lyu, Stefanus Jasin, Sajjad Najafi, and Huanan Zhang (alphabetically ordered)
Submitted to Operations Research.
Efficient UCB-Type Learning Algorithms for Lost-Sales Inventory Models with Lead Times and Censored Demand
Chengyi Lyu, Huanan Zhang, and Linwei Xin
Working paper.
TEACHING EXPERIENCES
University of Colorado Boulder
Class:
BCOR 2206 - Principles of Operations Management (Undergraduate)
Penn State
Class:
IE 570 - Supply Chain Engineering (Graduate)
IE 460 - Service Systems Engineering (Undergraduate)
University of Michigan
Class:
IOE 440 Operations Analysis & Management (Undergraduate)
CONFERENCES
Online Learning and Optimization for Revenue Management Problems with Add-on Discounts
INFORMS 2020, Virtual Meeting.
Multi-Product Price Optimization and Learning under a General Cascade Click Model with Filters
POMS 2019, Washington, DC.
IISE 2019, Orlando, FL.
INFORMS 2019, Seattle, WA.
Online Learning and Optimization of (Some) Cyclic Pricing Policies for Revenue Management with Patient Customers
INFORMS 2018, Phoenix, AZ.
POMS 2019, Washington, DC.
Closing the Gaps: An Online Learning Algorithm for Lost-Sales Inventory Systems with Lead Times
INFORMS 2017, Houston, TX.
MSOM 2017, Chapel Hill, NC.
POMS 2017, Seattle, WA.
Nonparametric Learning Algorithms for Optimal Base-Stock Policy in Perishable Inventory Systems with Censored Demand
INFORMS 2016, Nashville, TN.
Approximation Algorithms for Perishable Inventory Systems with Setup Costs
INFORMS 2014, San Francisco, CA.
Approximation Algorithms for Stochastic Inventory Control Problems with Regular and Expedited Supplies
INFORMS 2013, Minneapolis, MN.
Approximation Algorithms for Capacitated Stochastic Lot-Sizing Models with Fixed Ordering Cost
MSOM 2013, INSEAD, France.
Selected HONORS, AWARDS & Grants
Kolb Teaching Award, Leeds School of Business, 2020.
MHI/CICMHE Research Funding Program – Start-up Grants ($22,500)
Finalist, POMS-JD.com 2019 Best Data-Driven Research Paper Competition, 2019.
IOE Outstanding Graduate Student (one recipient per year), 2017, University of Michigan
Niuniu Ji Scholarship - Silver Award, 2011, CUHK
Charles K.Kao Research Exchange Scholarship, 2010, CUHK
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