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Shan Huang is currently an Assistant Professor at the Faculty of Business and Economics at the University of Hong Kong. Previously, she was an Assistant Professor at the Foster School of Business, University of Washington, Seattle. She also serves as a consultant for Tencent and is a Digital Fellow at the Stanford Digital Economy Lab.

 

Shan’s research centers on the digital economy, social networks, and causal (experimental) methods for managerial decision-making. She integrates large-scale field experiments (A/B tests, causal inference) with machine learning and large language models (LLMs) to gain insights into contemporary digital phenomena and to develop novel experimentation methods that enable more effective, data-driven decision-making.

 

She recently explores innovative approaches to enhance the external validity of experiments for product decisions, such as estimating long-term and representative treatment effects using data from short-term experiments. These methods aim to bridge the gap between experimental results and decision-making outcomes. Her empirical work examines how emerging social media platforms influence economic activities, including social advertising, social referrals, and content diffusion.

 

Her research has been published in leading management journals and presented at major conferences. Over the past decade, Shan has actively and closely collaborated with industry partners, particularly Tencent, to analyze and gain insights into various aspects of the digital landscape. She conducted the first A/B test at WeChat, which led to the development of Tencent’s initial A/B testing infrastructure, and played a key role in establishing the team for industry-academia collaboration at WeChat (Tencent). Shan earned her bachelor’s degree from Tsinghua University and her Ph.D. from the MIT Sloan School of Management.

Research Interests:

  • AI in Marketing, Social Networks, Causal and Experimentation Methods (A/B testing)

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Publications

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

    • Accepted at The Twenty-Fourth ACM Conference on Economics and Computation (EC'23)

    • under minor revision at Management Science 

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

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

  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, 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, The Twenty-Fifth ACM Conference on Economics and Computation (EC'24)

† corresponding author; *  co-first authors

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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, previously Kuaishou, Alibaba)

 

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