William Stamey
PhD Student, IT, Analytics, and Operations; Cusumano Family Fellow
IT, Analytics, and Operations
221 Mendoza
- Biography
- Background
- Publications
- Presentations
Will Stamey is an Analytics PhD candidate in his fifth year. Primarily, his research develops computational statistical methods that are tailored for decision-making problems, especially for causal inference in digital settings that entail high-frequency or high-dimensional human behavior data. Beyond this core work, he studies the impacts of AI agents on interactions between humans and develops measures for understanding how similarity across groups affects cooperation and success. Prior to joining the Analytics PhD Program, he received a B.B.A. from Baylor University in 2022 with majors in economics and math.
Education
BBA, Baylor University
"Fast Selection From Multiple Treatments: A Sequential Method for Principled Digital Experimentation", (With Ken Kelley, Bhargab Chattopadhyay, Tathagata Bandyopadhyay), Information Systems Research - Accepted (awaiting publication)
"Difference-in-Differences Subset Scan", (With Sriram Somanchi, Edward McFowland III), Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Datamining, 2025
"DiD-Scan: Discovering Subsets in Observational Causal Inference", Twenty-second Symposium on Statistical Challenges in Electronic Commerce Research (SCECR), 2026
"POP-Scan: Scanning Potential Outcomes Predictions for Discovering Effect Patterns in Megastudies", Experimentation and Evaluation in Operations Workshop at Harvard Business School, 2026