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Shan Huang is an Assistant Professor of Marketing at the Faculty of Business and Economics, The University of Hong Kong, a Digital Fellow at Stanford University’s Digital Economy Lab, and a consultant to Tencent. She earned her Ph.D. in Management Science from the MIT Sloan School of Management, an MSc from the University of British Columbia, and a B.BA from Tsinghua University.

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Her research examines technology-enabled marketing strategies, artificial intelligence in decision-making, and large-scale digital experimentation at the intersection of marketing and information technology. She integrates field experiments (A/B testing, causal inference) with machine learning and large language models (LLMs) to generate insights into digital phenomena and to design new methods that advance data-driven decision making. Empirically, her work investigates how social media platforms and algorithmic curation influence advertising effectiveness, social referrals, and content diffusion. Methodologically, she develops tools to estimate long-term and representative treatment effects from short-term experiments, and explores how historical experimental results can be generalized into interpretable insights for decision making using LLMs. Her work has appeared in Management Science, Marketing Science, and other leading management journals, as well as premier computer science venues such as ACM EC, and has been supported by over HKD 3 million in competitive research grants.

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Professor Huang views research, teaching, and practice as deeply interconnected. Since 2015, she has collaborated extensively with Tencent, launching WeChat’s first large-scale A/B test and co-developing its experimentation infrastructure. Her methodological innovations have been adopted by Tencent and ByteDance, directly influencing practice. At HKU, she designed and teaches Digital Experimentation Methods, a course that earned the Faculty Teaching Innovation Award in 2024. She is also co-authoring a forthcoming book with senior industry leaders, documenting China’s experience with experimentation and data-driven decision making for a global audience.

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Research Interests

  • Technology-Enabled Marketing Strategies and Decision-Making
    • AI in Marketing Decisions, Causal and Experimentation Methods (A/B testing), New Social Media Platforms, Computational Social Science, Social Networks

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Publications

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  1. Shan Huang*†, Chen Wang*, Yuan Yuan*, Jinglong Zhao* & Jingjing Zhang (industry author) (2025), Estimating Effects of Long- Term Treatments, Management Science, forthcoming

    • Abstract appears in proceedings of The Twenty-Fourth ACM Conference on Economics and Computation (EC'23)

  2. Yifan Yu*, Shan Huang*†, Yuchen Liu, & Yong Tan (2025), Emotions in Online Content Diffusion, Information Systems Research.

  3. Shan Huang† & Song Lin† (2024), Do More "Likes" Lead to More Clicks? Evidence from a Field Experiment on Social Advertising, Journal of Marketing.

  4. Shan Huang†, Sinan Aral, Yu Hu & Erik Brynjolfsson (2020). Social Advertising Effectiveness Across Products: A Large-Scale Field Experiment, Marketing Science, 39(6), 1142-1165.

  5. Hailiang Chen†, Yu Hu & Shan Huang (2019). Monetary Incentive and Stock Opinions on Social Media. Journal of Management Information Systems, 36(2), 391-417.​

  6. Chen Wang, Shichao Han (industry author) & Shan Huang†, Enhancing External Validity of Experiments with Ongoing Sampling,

    • Abstract appears in proceedings of The Twenty-Fifth ACM Conference on Economics and Computation (EC'24)

  7. Shan Huang† & Yi Ji, Algorithmic vs. Friend-based Recommendations in Shaping Novel Content Engagement: A Large-scale Field Experiment,

    • Abstract appears in proceedings of The Twenty-Fifth ACM Conference on Economics and Computation (EC'24)

† corresponding author;

* the authors are listed alphabetically or in reverse order of seniority

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Business Cases

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  1. Shan Huang†, Shipeng Yan, Zhenhui Jiang, & Minying Huang (2022), ESG at WeChat Pay to Support SMEs, Asia Case Research Centre

  2. Shan Huang†, Xiaoming Yuan, and Minying Huang (2025), Algorithm Innovation at Huawei Cloud, Asia Case Research Centre, forthcoming

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Research-in-progress (Highlight) 

 

LLM-based Causal Inference: A Multi-Agent System

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Book (in progress)

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Experimentation at Scale: Methods and Practice from China’s Tech Frontier

with Yunfei Han (Bytedance), Yong Wang (Tencent), and Kenny Xie (Google)

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Recent Talks​

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  • Invited Talk @ City University of Hong Kong

  • Invited Talk @ Tencent IEG Globe, Palo Alto, CA

    • Estimating Long-term Treatment Effects, June 2025.

  • Tech Talk (company-wide) @ LinkedIn, Mountain View, CA

    • Two Approaches for Estimating Long-term Treatment Effects with Applications at WeChat, June 2025.

  • Invited Talk @ Yale Marketing Seminar, New Haven, CT

    • Enhancing External Validity of Experiments with Ongoing Sampling, June 2025 ​​

  • HK Quant Marketing Mini-Conference, Keynote Speaker, Hong Kong​

    • Enhancing External Validity of Experiments with Ongoing Sampling, May 2025

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Media Coverage​

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