Colloquium - Yichen Qin - February 26, 2026

Speaker: Yichen Qin, University of Cincinnati
Date/Time: Thursday, February 26, 2026, 10:00 AM - 11:00 AM ET

Title: Bootstrapping Random Walk Sample Networks

Abstract: In network analysis, we often use a statistic on the sample network, such as motif density, to make inference about the population. Due to practical constraints such as computation and privacy, traditional random vertex sampling is often infeasible, and the network may only be accessible through traversal sampling methods, such as random walk sampling. However, due to the complex nature of the random walk sampling, the analytical form of the sampling distribution of the statistic is often unavailable or mathematically intractable, preventing us from conducting inference. To address this issue, we propose to bootstrap the random walk sample network to approximate the sampling distribution for inference and establish its bootstrap consistency. In addition, by establishing and comparing the asymptotic properties of motif densities under random walk and random vertex sampling, we show that many existing network bootstrap methods are systematically biased under the random walk case. Simulation studies and a real-world network analysis show that the proposed method outperforms existing methods.

Bio: Yichen Qin is a Professor of Business Analytics in the Department of Operations, Business Analytics, and Information Systems (OBAIS) at the Lindner College of Business at the University of Cincinnati. He earned his Ph.D. in Applied Mathematics and Statistics and M.S.E. in Financial Mathematics from Johns Hopkins University. His research focuses on computational statistics, network analysis, model selection, and design of experiments. His work has appeared in the Journal of the American Statistical Association, Biometrika, Biometrics, Neural Information Processing Systems, etc. At UC, he coordinates the PhD program in OBAIS and provides consulting service to local hospitals, department stores, and insurance companies. His methodology and application work has been awarded Transdisciplinary Research Leadership Program, INFORMS Analytics Society Innovative Applications in Analytics Award, etc.

Website: https://www.business.uc.edu/faculty-research/obais/faculty/yichen-qin.html