Barry L. Nelson
Walter P. Murphy Professor
Department of Industrial Engineering & Management Sciences
McCormick School of Engineering and Applied Science
2145 Sheridan Road, Room M326
Evanston, IL 60208-3119
Distinguished Visiting Scholar
Lancaster University Management School
- Research and Teaching Interests
- Important Links
- Publications, Working Papers and Books
- Detailed Vitae (pdf)
- Family Pictures
- BA, Mathematics and Computer Science, DePauw University
- MS, PhD, Industrial Engineering, Purdue University
Research and Teaching Interests
Nelson studies the design and analysis of computer simulation experiments, particularly issues of statistical efficiency (such as variance-reduction techniques), multivariate output analysis (such as multiple-comparison procedures and simulation optimization), model risk (such as uncertainty quantification due to input modeling), input modeling (such as modeling and generation of nonstationary arrival processes and frequentist model averaging), metamodeling (such as stochastic kriging) and simulation analytics (such as virtual statistics). His application areas include financial engineering, computer performance modeling, quality control, manufacturing and transportation systems. He is a Fellow of INFORMS and IISE, and received the 2019 IISE David F. Baker Distinguished Research Award.
- computer simulation of stochastic systems
- stochastic processes
- statistical learning
Nelson teaches courses on computer simulation and statistical learning. He was named McCormick teacher of the year in 1998 and 2007, was elected to the 2002, 2003 and 2007 ASG Faculty Honor Rolls, received the 2003 Northwestern Alumni Association Excellence in Teaching Award, was given the 2004 IISE Operations Research Division Award and the 2019 Modeling and Simulation Division Award for Excellence in the Teaching, and was a Charles Deering McCormick Professor of Teaching Excellence.
- Parallel Adaptive Survivor Selection for Very Large-Scale Simulation Optimization from 2019 INFORMS Applied Probability Conference.
- Video of Nelson's WSC 2017 Keynote Address and Slides (pdf)
- Video of Nelson's 2018 Pritsker Lecture at Purdue
- Video of Nelson's WSC 2013 Titans of Simulation Talk
- Video of Nelson's Omega Rho Lecture at INFORMS 2011
- PI with Andreas Waechter and Eunhye Song on NSF Grant "Adaptive Gaussian Markov Random Fields for Large-scale Discrete Optimization via Simulation."
- PI on NSF Grant "Green Simulation."
- PI with Emily Lada and Bahar Biller (SAS Institute) on NSF GOALI Grant "Simulation Analytics."
- PI with Peiling Wu (GM) on General Motors Grant "Quantifying the Uncertainty in the Content Optimization Analysis."
- PI with Dennis Pegden (Simio LLC) on NSF GOALI Grant "Quantifying Input Uncertainty in Stochastic Simulation."
- Co-PI with Bruce Ankenman and Jeremy Staum on NSF Grant "Stochastic Kriging: Modeling and Controlling Uncertainty in Simulation."
- Co-PI with Wally Hopp on General Motors Grant "Strategic Decision Making Support Over the Manufacturing Life Cycle."
- Co-PI with Jeremy Staum on National Science Foundation Grant "Simulating Coherent Risk Measures."
- Co-PI with Mike Taaffe on National Science Foundation Grant "QNATS - The Queueing Network Approximator for Time-Dependent Systems."
- Co-PI with Bruce Ankenman, John Fowler and Gerald Mackulak on Semiconductor Research Corporation Grant "Multi-product Cycle Time and Throughput Evaluation via Simulation on Demand."
- Co-PI with Sigrun Andradottir on the National Science Foundation Grant A Framework for Effective Optimization via Simulation.
- Co-PI with Bruce Ankenman on General Motors Grant "A Simulation Design and Analysis Environment for GM." (completed)
- Co-PI with Bruce Ankenman, John Fowler and Gerald Mackulak on National Science Foundation Grant Procedures for Efficient Cycle Time-Throughput Curve Generation. (completed)
- Co-PI with Joseph Schofer on TCRP Grant B-23 "Resource Requirements for Demand-Responsive Transportation Services." (completed)
- PI on General Motors Grant "A Simulation Framework for Vehicle Distribution Systems." (completed)
- Co-PI with David Goldsman on the National Science Foundation Grant Comparisons via Stochastic Simulation, with Applications to Manufacturing and Services. (completed)
- Co-PI with James R. Wilson on the National Science Foundation Grant A Comprehensive Framework and Software for Simulation Input Modeling. (completed)
- PI on Scenario Generation and Evaluation in Discrete-Event Simulation sponsored by JGC Corporation. (completed)
Publications and BooksRanking & Selection, Multiple Comparisons
Input Modeling and Input Uncertainty
Optimization via Simulation
Click here to download FMAdist, an R package for creating simulation input models via frequentist model averaging.
Click here to download sensitivity, an R package for global sensitivity analysis that contains our work on Shapley effects.
Click here to download Industrial Strength Compass software for optimization via simulation.
Click here to download ARTAFACTS and ARTAGEN software for time series input modeling.
Click here to download VARTA software for multivariate time series input modeling.
Click here to download Maple procedures to analyze Ph(t)/Ph(t)/Infinity queues.
- IEMS 304 Statistical Learning for Data Analysis
- IEMS 317 Discrete-Event Systems Simulation
- IEMS 415 Computer Simulation for Risk and Operations Analysis (MEM Course)
- IEMS 435 Stochastic Simulation
- IEMS 465 Simulation Experiment Design and Analysis
- STOR 606 Stochastic Simulation (Lancaster University)
- Design and analysis of discrete-event simulation experiments, emphasizing input modeling, experimental design and output analysis.
- Ranking and selection methods.
- Spreadsheet simulation, emphasizing how to select probablity distributions based on little or no data.
- Use of basic queueing models.
last update 2/6/2020