Chaofan Zhai

Chaofan Zhai

PhD Candidate
Information & Decision Sciences

Education:

  • Ph.D. 2026(expected)
    Information & Decision Science, University of Minnesota
  • M.S. 2020
    Applied Data Science, University of Southern California
  • B.S. 2017
    Information System, Shanghai University of Finance & Economics

Expertise:

  • Topics : AI + Online Education , Human-AI Collaboration, AI + Influencer Economy
  • Machine learning
  • Field/Online Experiment
  • Generative AI (Vibe Coding/RAG/MCP)
  • Analytical Modeling

Biography

I am a Ph.D. Candidate in Information & Decision Sciences at the Carlson School of Management, University of Minnesota. My advisor is Professor Ravi Bapna.

I study AI-enabled decision-making from both a "how" perspective and a "what" perspective:

  • Algorithmic Design ("How"): I develop and deploy innovative machine learning algorithms to address real-world challenges, such as learning design in online education, human-AI collaboration design in generative AI contexts, and matching design in multi-stakeholder marketplaces.
  • Economic Impact("What"): I use field and online experiments to rigorously measure the real-world impact of these AI designs on individual decision quality and platform economic outcomes.

My aspiration is to conduct research that has a real impact on supporting individual and organizational decision-making.

 



HONORS AND AWARDS

  • The Winner of WITS Best Dissertation Award (Dec 2024)
    • Dissertation: "Three Essays on Overcoming Cognitive Frictions in Online Education"
  • Selected Participant for 2024 ICIS Doctoral Consortium (Aug 2024)
  • Carlson School Dissertation Fellowship ($32,000) (April 2024)
  • Dean's Small Grant for Research ($10,000) (Nov 2023)
  • Carlson School of Management Ph.D. Student Teaching Award (August 2023)
  • Ph.D. Student Conference/Travel Fellowship (2020 – Now)
  • Carlson and Willoughby IDS Ph.D. Fellowship (2020 – Now)
  • Ph.D. Student Summer Research Fellowship (2020 – Now)

Working Papers

  • Chaofan Zhai, Ravi Bapna, Alok Gupta, "Human-Generative AI Collaboration in Business Analytics Problem Solving: A Large-Scale Online Experiment"
    • Google Cloud Research Credit, 2024
  • Chaofan Zhai, Yicheng Song, Ravi Bapna, "Reinforcement Learning for Sustainable Learning in Online Education: A Large-scale Field Experiment"
    • Workshop on Information Technologies and Systems (WITS), Bangkok, 2024
    • Statistical Challenges in Electronic Commerce Research (SCECR), Lisbon, 2024
    • Production and Operations Management Society (POMS) Minneapolis, 2024
    • INFORMS Annual Conference, Seattle, 2024
    • Carlson School Dean's Small Grant ($10,000), 2023
  • Chaofan Zhai, Xuan Bi, Angela Aerry Choi, Chad Yi-Chun Ho, "A Customer-Aware Recommender System for Influencer Marketing: A Large-scale Field Experiment"
    • Statistical Challenges in Electronic Commerce Research (SCECR), Cyprus, 2025
  • Chaofan Zhai, Amit Mehra, Ravi Bapna, "Pricing Strategies in Online Education"
    • Conference on Information Systems and Technology (CIST), Indianapolis, 2022
  • Chaofan Zhai, Xuan Bi, Mochen Yang, "Incentivization of Federated Learning: A Novel Stackelberg Game"
    • INFORMS Annual Conference, Indianapolis, 2022

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