题　目：Experimental design under interference: live-interaction platforms and beyond

嘉　宾：司念 助理教授 香港科技大学

主持人：许欢 教授 上海交通大学安泰经济与管理学院

时　间：2025年4月16日（周三）14:00-15:30

地　点：安泰楼A507室

内容简介：

This first part of this talk will focus on experimental design problems in live-interaction platforms, which are commonly found in the online gaming industry and anonymous social networks. These platforms involve users being matched with others for activities such as games or social interactions, resulting in an interdependence of users' metrics on the treatment assignments of their counterparts. We construct a stochastic market model and develop its mean field limit to analyze the experimental dynamics in such platforms. Our focus is on two randomization strategies: user randomization and match randomization. We demonstrate that under Markovian user behavior and homogeneous treatment effects, match randomization can provide unbiased estimations. However, significant biases may arise when these conditions are not met. On the other hand, user randomization is generally biased but exhibits greater resilience to model inaccuracies. We then propose a simple linear regression estimator under user randomization and demonstrate that this estimator consistently outperforms alternatives in various situations. It is a joint work with Xiao Lei (HKU) and Chenran Weng (UC Berkeley). The second part of the talk will briefly touch on other applications of experimental design under interference in operational contexts, including job scheduling in data centers, recommendation systems in online platforms, inventory control in warehouses, and choice-based revenue management.

演讲人简介：

Nian Si is an assistant professor at HKUST IEDA. He was a postdoctoral principal researcher at the University of Chicago Booth School of Business, working with Professor Baris Ata. He obtained my Ph.D. in the Department of Management Science and Engineering (MS&E) at Stanford University, where he was advised by Professor Jose Blanchet and closely worked with Professor Ramesh Johari. He was a member of the Stanford Operations Research Group. Previously, He obtained a B.A. in Economics and a B.S. in Mathematics and Applied Mathematics both from Peking University in 2017. His research lies at the interface of operations research, statistics, machine learning, and economics. He is also interested in real-world operational problems arising from online platforms, including A/B tests, recommendation systems, online advertising, cloud computing, AI, etc.

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