معرفی
Mengxiao Zhang is an Assistant Professor in the Department of Business Analytics at the Tippie College of Business, University of Iowa, holding this position since August 2024. His research develops theoretically grounded machine learning algorithms for practical business applications, with expertise spanning online learning, bandit problems, and game-theoretic optimization.
His academic foundation includes:
- Ph.D. in Computer Science from the University of Southern California (2018-2024), advised by Prof. Haipeng Luo
- Bachelor's degree from Peking University (2014-2018), advised by Prof. Liwei Wang
Zhang's research bridges theoretical machine learning with operational business challenges, focusing on adaptive algorithms that maintain performance guarantees in non-stationary environments. His work addresses core problems in regret minimization, efficient exploration, and equilibrium computation, with increasing emphasis on supply chain optimization, auction design, and fair multi-agent systems. He designs methods that function effectively under constraints like delayed feedback, budget limitations, and unknown demand distributions.
Analysis of his 15 most recent publications (2022-2025) reveals a consistent trajectory toward business-relevant applications while maintaining theoretical rigor. Key trends include contextual bandit extensions for advertising auctions, supply chain optimization under uncertainty, and fairness-aware multi-agent learning. His contributions appear in top-tier venues including COLT, ICML, and NeurIPS, with notable recognition including a NeurIPS 2020 Oral presentation.
No scientific awards are documented in the provided materials.
Zhang teaches Database Management (BAIS-3200) at the University of Iowa and previously served as teaching assistant for multiple graduate algorithms and machine learning courses at USC. No information regarding research grants or student advising is available in the source materials.
No dedicated laboratory or research team structure is specified in the provided information.
