Chaofan Zhai
PhD Candidate
Information & Decision Sciences
Contact
Education:
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Ph.D. 2026(expected)Information & Decision Science, University of Minnesota
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M.S. 2020Applied Data Science, University of Southern California
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B.S. 2017Information System, Shanghai University of Finance & Economics
Expertise:
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Topics : AI + Online Education , Human-AI Collaboration, AI + Influencer Economy
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Machine learning
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Field/Online Experiment
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Generative AI (Vibe Coding/RAG/MCP)
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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