Yufeng Zheng

Ph.D. Candidate · Operations Management & Statistics
Rotman School of Management, University of Toronto

Yufeng
Zheng

I study how learning systems and autonomous agents should be designed, deployed, and governed to improve operations and strategic decision-making.

CV Google Scholar
Zheng et al. — arrivals simulator
OperationsAI agentsFoundation modelsOnline learningSimulationExperimentsMarkets & gamesMachine learning

Research

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AI Agents in the Economy, Organizations, and Science

AI agents increasingly act as products, algorithms, productive assets, workers, collaborators, and delegated decision-makers.

1 paper

Foundation Models and Learning for Operational Systems

I build reusable models that learn the dynamics of operational systems such as queues, arrivals, inventories, and service processes, simulate them, and transfer decision strategies across related problems.

5 papers

Experiments, Markets, and Games

I study decisions that learn from people and markets: experiments whose traffic is scarce, platforms whose users respond, and markets where firms, algorithms, and users learn and react strategically.

2 papers

News

  1. 2026

    This website is being rebuilt, with a research chat grounded in my papers.

  2. 2025

    “A Doubly Stochastic Simulator with Applications in Arrivals Modeling and Simulation” published in Operations Research.

  3. 2025

    “LOLA: LLM-Assisted Online Learning Algorithm for Content Experiments” published in Marketing Science.

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