Journal Publications and Working Papers
Y. Lin, H. Zhang, R. Zhang, Z. M. Shen, "Non-progressive Diffusion on Social Networks: Approximation and Applications (2025)" Accepted at Management Science.
− Preliminary version accepted at the Twenty-fifth ACM Conference on Economics and Computation (EC'24)
− Finalist, INFORMS Minority Issues Forum Poster Competition, 2023
− Finalist, the 18th INFORMS Data Mining and Decision Analytics (DMDA) Workshop Best Paper Competition Award (Theoretical Track), 2023.
− Accepted to INFORMS Workshop on Data Science, 2023
− First-Place Price, Thirteen POMS-HK International Conference Best Student Paper Award, 2022
Z. Ye, Z. Zhang, D. Zhang, H. Zhang, R. Zhang, "Deep Learning Based Causal Inference for Large-Scale Combinatorial Experiments: Theory and Empirical Evidence (2025)," Accepted at Management Science.
− Preliminary version accepted at the Twenty-Fourth ACM Conference on Economics and Computation (EC'23), 2023
− Accepted to INFORMS Workshop on Data Science, 2023
− Second Place, CSAMSE Annual Conference Best Paper Award, 2023
− Winner, Best Student Paper of Social Media Analytics 2023
Y. Wang, M. Li, N. Ma, H. Zhang, "Product Service Outsourcing: Impact of Environment Uncertainty and Partial Observability (2024)." Accepted at Manufacturing and Service Operations.
M. Wang, H. Zhang, P. Rusmevichientong, Z. M. Shen, “Optimizing Offline Product Design and Online Assortment Policy: Measuring the Relative Impact of Each Decision (2025).” Management Science, 71(5), 3641-4531.
− Finalist, Jeff McGill Student Paper Award, 2022
− Second Place, OR/MS Tomorrow Mini-poster Competition, 2022
Y. Lin, M. Wang, H. Zhang, R. Zhang, Z. M. Shen, “Content Promotion for Online Content Platforms with Network Diffusion Effect (2024).” Manufacturing & Service Operations Management, 26(3), 797-1187.
− Finalist, INFORMS Minority Issue Forum Paper Competition, 2024
− Winner, Best Student Paper of INFORMS Social Media Analytics 2022
Z. Zeng, H. Dai, D. Zhang, Z.M. Shen, Z. Xu, H. Zhang, R. Zhang, “Social Nudges Boost Productivity on Online Platforms: Evidence from Field Experiments (2023),” Management Science, 69(9), 4973-5693.
− Finalist, MSOM Student Paper Competition, 2023
Z. Ye, D. Zhang, H. Zhang, R. Zhang, X, Chen, “Cold Start on Online Advertising Platforms: Data-Driven Algorithms and Field Experiments (2022).” Management Science, 69(7), 3759-4361.
− Finalist, INFORMS Revenue Management and Pricing (RMP) Section 2020 Student Paper Prize (Awarded to Coauthor Zikun Ye)
− Spotlighted presentation in INFORMS RMP Conference (2021)
M. Gopalakrishnan, H. Zhang, Z. Zhang, "Multi-Product Pricing under the Multinomial Logit Model with Local Network Effects (2022)." Decision Sciences, 54(4), 447-466.
L. Y. Chu, H. Nazerzadeh, H. Zhang, “Position Ranking and Auctions for Online Marketplaces (2020).” Management Science, 66(8): 3295 - 3798, 2020.
H. Zhang, P. Rusmevichientong, H. Topaloglu, “Assortment Optimization under the Pairwise Combinatorial Logit Model (2020).” Operations Research, 68(3): 655 - 964.
H. Zhang, P. Rusmevichientong, H. Topaloglu, “Multi-Product Pricing under Generalized Extreme Value Models with Homogeneous Price Sensitivity Parameters (2018)." Operations Research, 66(6): 1559 - 1570, 2018.
H. Zhang, H. Piri, W. T. Huh, H. Li, “Assortment Optimization Under Multiple-Discrete Customer Choices,” major revision at Manufacturing & Service Operations Management.
Z. Chen, H. Zhang, H. Li, S. Webster, "Multi-Objective Assortment Optimization: Revenue, Risk, Customer Utility and Beyond," major revision at Management Science.
M. Wang, D. Zhang, H. Zhang, "Harnessing Large Language Models for Market Research: A Data-augumentation Approach," submitted to Marketing Science.
− Sponsored by OpenAI's Researcher Access Program ($5,000)
− Preliminary version accepted at NeurIPs Workshop on Statistical Frontiers in LLMs and Foundation Models, 2024
Y. Huang, J. Feldman, H. Zhang, "Basic Reusability and Beyond: Joint Inventory and Online Assortment Optimization with Reusable Resources," submitted to Management Science.
N. Ma, H. Zhang, Y. Wang, ``Managing Supply Disruption Risk: Selecting Unreliable Suppliers under Cardinality Constraints," submitted to Operations Research.
Refereed Conference Proceedings
Z. Ye, Z. Zhang, D. Zhang, H. Zhang, R. Zhang, Deep Learning Based Causal Inference for Large-Scale Combinatorial Experiments: Theory and Empirical Evidence, Twenty-Fourth ACM Conference on Economics and Computation (EC'23), 2023
J. Cao, H. Zhang, Q. Zheng, “Retaining Customers by Data Mining: A Telecomunication Carrier’s Case Study in China,” 2010 International Conference on E-Business and E-Government, 3141 - 3144, 2010
H. Bastani, D. Zhang, H. Zhang, “Applied Machine Learning in Operations Management,” in: V.Babich, J.Birge, G.Hilary (eds) Innovative Technology at the Interface of Finance and Operations, Springer Series in Supply Chain Management, Springer Natures, forthcoming, 2021
