Overview
David Banks was the coordinating editor of the Journal of the American Statistical Association. He co-founded the journal Statistics and Public Policy and served as its editor. He co-founded the American Statistical Association's Section on National Defense and Homeland Security, and has chaired that section, as well as the sections on Risk Analysis and on Statistical Learning and Data Mining. In 2003 he led a research program on Data Mining at the Statistical and Applied Mathematical Sciences Institute; in 2008, he led a research program at the Isaac Newton Institute on Theory and Methods for Complex, High-Dimensional Data; in 2012, he led another SAMSI research program, on Computational Advertising. He has published 74 refereed articles, edited eight books, and written four monographs.
David Banks is past-president of the Classification Society, and has twice served on the Board of Directors of the American Statistical Association. He is currently the president of the International Society for Business and Industrial Statistics. He is a fellow of the American Statistical Association and of the Institute of Mathematical Statistics. He recently won the American Statistical Association's Founders Award.
His research areas include models for dynamic networks, dynamic text networks, adversarial risk analysis (i.e., Bayesian behavioral game theory), human rights statistics, agent-based models, forensics, and certain topics in high-dimensional data analysis.
Current Appointments & Affiliations
Recent Publications
Foreword to the Special Issue on Data Science in Business and Industry
Journal Article Applied Stochastic Models in Business and Industry · May 1, 2025 Full text CiteIndustrial Statistics in the Knowledge Economy
Journal Article Applied Stochastic Models in Business and Industry · May 1, 2025 Industrial statistics grew up in an era when manufacturing was the primary engine of commerce. Today, the driver is information technology. This paper discusses how statisticians need to adapt to contribute to this new business model, with particular empha ... Full text CiteIs There a Future for Stochastic Modeling in Business and Industry in the Era of Machine Learning and Artificial Intelligence?
Journal Article Applied Stochastic Models in Business and Industry · March 1, 2025 The paper arises from the experience of Applied Stochastic Models in Business and Industry which has seen, over the years, more and more contributions related to Machine Learning rather than to what was intended as a stochastic model. The very notion of a ... Full text CiteRecent Grants
NRT-HDR: Harnessing AI for Autonomous Material Design
Inst. Training Prgm or CMECo-Principal Investigator · Awarded by National Science Foundation · 2020 - 2026Adversarial Risk Analysis for Optimal Obstacle Evasion
ResearchPrincipal Investigator · Awarded by Auburn University · 2022 - 2025HDR TRIPODS: Innovations in Data Science: Integrating Stochastic Modeling, Data Representation, and Algorithms
ResearchSenior Investigator · Awarded by National Science Foundation · 2019 - 2023View All Grants