Jim Wilson
Professor Emeritus
- Phone: 919.515.2362
- Email: jwilson@ncsu.edu
James Wilson has been a member of the Industrial and Systems Engineering faculty at North Carolina State University since 1991. He served as head of the department from 1999 to 2007.
Research Interests
Jim Wilson’s research interests include probabilistic and statistical issues in the design and analysis of large-scale simulation experiments, including: modeling, estimation, and generation of stochastic input processes; analysis of output processes; improving simulation efficiency using variance reduction techniques; optimization using multiple-comparison and search procedures; and applying all these techniques to the analysis of production systems.
Education
| Degree | Program | School | Year |
|---|---|---|---|
| Ph.D. | Doctor of Philosophy | Purdue University | 1979 |
| MS | Master of Science | Purdue University | 1977 |
| BA | Bachelor of Arts | Rice University | 1970 |
Honors and Awards
- 2022 | Top North American Researcher in Industrial and Manufacturing Engineering, ADScientific Index
- 2013 | David F. Baker Distinguished Research Award, Institute of Industrial Engineers
- 2011 | Distinguished Contributions Award, Association for Computing Machinery Special Interest Group on Simulation
- 2011 | IIE Transactions Best Paper Award in Operations Engineering and Analysis, Institute of Industrial Engineers
- 2009 | Faculty Award, NC State University Libraries
- 1995 | C. A. Anderson Outstanding Faculty Award, ISE Department at NC State University
- Fellow, Institute of Industrial Engineers
- Fellow, Institute for Operations Research and the Management Sciences
Discover more about Jim Wilson
Publications
- A SEQUENTIAL METHOD FOR ESTIMATING STEADY-STATE QUANTILES USING STANDARDIZED TIME SERIES
- Lolos, A., Boone, J. H., Alexopoulos, C., Goldsman, D., Dingec, K. D., Mokashi, A. C., & Wilson, J. R. (2022), 2022 WINTER SIMULATION CONFERENCE (WSC), pp. 73–84. https://doi.org/10.1109/WSC57314.2022.10015283
- ESTIMATING CONFIDENCE REGIONS FOR DISTORTION RISK MEASURES AND THEIR GRADIENTS
- Lei, L., Alexopoulos, C., Peng, Y., & Wilson, J. R. (2022), 2022 WINTER SIMULATION CONFERENCE (WSC), pp. 13–24. https://doi.org/10.1109/WSC57314.2022.10015404
- CONFIDENCE INTERVALS AND REGIONS FOR QUANTILES USING CONDITIONAL MONTE CARLO AND GENERALIZED LIKELIHOOD RATIOS
- Lei, L., Alexopoulos, C., Peng, Y., & Wilson, J. R. (2020), 2020 WINTER SIMULATION CONFERENCE (WSC), pp. 2071–2082. https://doi.org/10.1109/WSC48552.2020.9383910
- Improving chemotherapy infusion operations through the simulation of scheduling heuristics: a case study
- Slocum, R. F., Jones, H. L., Fletcher, M. T., McConnell, B. M., Hodgson, T. J., Taheri, J., & Wilson, J. R. (2020), Health Systems, 2, 1–16. https://doi.org/10.1080/20476965.2019.1709908
- STEADY-STATE QUANTILE ESTIMATION USING STANDARDIZED TIME SERIES
- Alexopoulos, C., Boone, J. H., Goldsman, D., Lobos, A., Dingec, K. D., & Wilson, J. R. (2020), 2020 WINTER SIMULATION CONFERENCE (WSC), pp. 289–300. https://doi.org/10.1109/WSC48552.2020.9384130
- Modeling and Simulation of Nonstationary Non-Poisson Arrival Processes
- Liu, R., Kuhl, M. E., Liu, Y., & Wilson, J. R. (2019), INFORMS JOURNAL ON COMPUTING, 31(2), 347–366. https://doi.org/10.1287/ijoc.2018.0828
- Probabilistic sensitivity analysis on Markov models with uncertain transition probabilities: an application in evaluating treatment decisions for type 2 diabetes
- Zhang, Y., Wu, H., Denton, B. T., Wilson, J. R., & Lobo, J. M. (2019), Health Care Management Science, 22(1), 34–52. https://doi.org/10.1007/S10729-017-9420-8
- Sequest: A Sequential Procedure for Estimating Quantiles in Steady-State Simulations
- Alexopoulos, C., Goldsman, D., Mokashi, A. C., Tien, K.-W., & Wilson, J. R. (2019), OPERATIONS RESEARCH, 67(4), 1162–1183. https://doi.org/10.1287/opre.2018:1829
- Simulation model of the relationship between cesarean section rates and labor duration
- Hicklin, K. T., Ivy, J. S., Wilson, J. R., Cobb Payton, F., Viswanathan, M., & Myers, E. R. (2019), Health Care Management Science, 22(4), 635–657. https://doi.org/10.1007/s10729-018-9449-3
- Simulation-based Evaluation On Integrating Additive Manufacturing Capability In A Deployed Military Environment
- Moore, T. A., McConnell, B. M., & Wilson, J. R. (2018), Proceedings of the 2018 Winter Simulation Conference, 3721–3729. https://doi.org/10.1109/wsc.2018.8632474
