Professor of the Practice of Statistical Science
David Banks obtained an M.S. in Applied Mathematics from Virginia Tech in 1982, followed by a Ph.D. in Statistics in 1984. He won an NSF Postdoctoral Research Fellowship in the Mathematical Sciences, which he took at Berkeley. In 1986 he was a visiting assistant lecturer at the University of Cambridge, and then joined the Department of Statistics at Carnegie Mellon in 1987. In 1997 he went to the National Institute of Standards and Technology, then served as chief statistician of the U.S. Department of Transportation, and finally joined the U.S. Food and Drug Administration in 2002. In 2003, he returned to academics at Duke University.
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.
Appointments and Affiliations
- Professor of the Practice of Statistical Science
Contact Information
- Office Location: 210A Old Chemistry Building, Duke University, Durham, NC
- Office Phone: +1 919 423 0792
- Email Address: david.banks@duke.edu
- Websites:
Education
- B.A. University of Virginia, 1977
- M.S. Virginia Polytech Institute and State University, 1980
- Ph.D. Virginia Polytech Institute and State University, 1984
Courses Taught
- STA 993: Independent Study
- STA 891: Topics for Preliminary Exam Preparation in Statistical Science
- STA 693: Research Independent Study
- STA 611: Introduction to Mathematical Statistics
- STA 521L: Predictive Modeling and Statistical Learning
- STA 493: Research Independent Study
- STA 211: The Mathematics of Regression
- STA 110FS: Focus Program - Introductory Special Topics in Statistics
- STA 101L: Data Analysis and Statistical Inference
- ME 555: Advanced Topics in Mechanical Engineering
- FOCUS 195FS: Special Topics in Focus
In the News
Representative Publications
- Caballero, W., J. Cooley, D. Banks, and P. Jenkins. “A BEHAVIORAL APPROACH TO REPEATED BAYESIAN SECURITY GAMES.” Annals of Applied Statistics 18, no. 1 (March 1, 2024): 199–223. https://doi.org/10.1214/23-AOAS1786.
- LeBlanc, P. M., D. Banks, L. Fu, M. Li, Z. Tang, and Q. Wu. “Recommender Systems: A Review.” Journal of the American Statistical Association 119, no. 545 (January 1, 2024): 773–85. https://doi.org/10.1080/01621459.2023.2279695.
- Banks, David, and Jennifer L. Clarke. “C. R. Rao (1920-2023).” Science (New York, N.Y.) 382, no. 6672 (November 2023): 771. https://doi.org/10.1126/science.adl1762.
- Banks, D., and F. Guo. “Foreword to the special issue on “Statistics of the Autonomous Vehicles”.” Applied Stochastic Models in Business and Industry 39, no. 5 (September 1, 2023): 628. https://doi.org/10.1002/asmb.2817.
- Banks, D., and Y. C. Liu. “Discussion of “Some statistical challenges in automated driving systems”.” Applied Stochastic Models in Business and Industry 39, no. 5 (September 1, 2023): 653–56. https://doi.org/10.1002/asmb.2797.