Behavioral Intelligence Lab
​行为智能实验室
The Behavioral Intelligence Lab works toward a human-centered future where AI truly serves human wellbeing. Many of the hardest problems in today's wellbeing crisis are behavioral: people who need care don't seek it, don't stay with it, and are rarely reached by the services that could catch problems early and intervene in time. At bottom, these are problems of measurement, demand, matching, and engagement — and they are the problems we work on with AI.
We develop the science and methods for understanding how humans and AI agents behave and make decisions. We use that understanding to match people with the care, services, and products they need, to keep them engaged, and to turn behavioral data into instruments of care — so that technologies built to raise our productivity can also learn to care for human minds.
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Our members are from multidisciplinary backgrounds, including computer science, economics, quantitative marketing, cognitive science, and psycholinguistics. We work to be a place where these different ways of thinking sharpen one another.
Research Theme
1. Computational Behavioral Science of AI and Human
We model, analyze, and explain the behavior of human and AI agents, as service providers or consumers, from individuals to markets. Recent works:
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Behavioral alignment and deviation between humans and AI agents
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Optimizing AI memory for user engagement
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Simulation and evaluation of synthetic patients
2. AI for Mental and Social Wellbeing
We hope our research can contribute to a human-centered future in which AI technology serves human wellbeing, especially from mental and social perspectives. Recent works:
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Building multi-agent screening systems for mental wellbeing
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Designing AI-assisted interventions for mental wellbeing
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Human–AI affective relationships for social wellbeing
Funding
We would like to thank our corporate sponsors and the funding agencies (the HK Research Grants Council, HKUST, MSI) for supporting our research.
Join Us
Postdoc, PhD, and RA positions are available. We look for candidates who share our research interests and have relevant research experience. If interested, please email me a copy of your resume, transcripts, papers, and other relevant materials. ​​
Selected Working Papers and Publication
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"Bonding with AI: Investigating the Love Relationships between Humans and AI Companions"
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Working paper with Hang Xu, Mengze Shi (2026)
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"A Randomized Experiment on AI Companion Use and Real-life Romantic Relationships"
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Working paper with Jiaming Jiang, Zoey Jiang, Kannan Srinivasan, George Loewenstein (2026)
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"Welfare Implications of Democratization in Content Creation: Generative AI and Beyond."
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Tianxin Zou, Zijun (June) Shi, Yue Wu (2026)
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Working paper with Xinyi Sun, Song Lin (2026)
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Information Silos on Social Media: Experimental Evidence from TikTok
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Working paper with Tianyu Han, Wenbo Wang (2026)
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The Effect of Voice AI on Digital Commerce
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Chenshuo Sun, Zijun (June) Shi, Xiao Liu, Anindya Ghose (2025)
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Information Systems Research, 36(2):1147-1166.
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On the Role and Design of Resale Royalties
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Working paper with Wenxiao Yang, Song Lin (2025)
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Gender-Neutral Marketing: Evidence from a Leading E-Commerce Platform
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Working paper with Jiaqi Chen, Tong Guo, Shuo Zhang (2025)​
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​How Do Fast Fashion Copycats Affect the Popularity of Premium Brands? Evidence from Social Media
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Zijun (June) Shi, Xiao Liu, Dokyun Lee, Kannan Srinivasan (2023).
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Journal of Marketing Research, 60(6), 1027-1051.​
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Hype News Diffusion and Risk of Misinformation: The Oz Effect in Healthcare
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Zijun (June) Shi, Xiao Liu, Kannan Srinivasan (2022).
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Journal of Marketing Research, 59(2), 327-352.
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Winner, Paul E. Green Award, 2023
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Winner, AMA MR-SIG Don Lehmann Award, 2023
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Design of Platform Reputation System: Optimal Information Disclosure
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Zijun (June) Shi, Kannan Srinivasan, Kaifu Zhang (2022).
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Marketing Science, 42(3), 500-520.​​​
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Freemium as an Optimal Strategy for Market Dominant Firms​
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Zijun (June) Shi, Kaifu Zhang, Kannan Srinivasan (2019).
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Marketing Science, 38(1), 150-169.
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Achim Ingo Czerny, Zijun (June) Shi, Anming Zhang (2016).
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Transportation Research Part A, Vol. 91 (September), 260-272.
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Alumni