Marvin Nakayama
Marvin Nakayama
Professor, Computer Science
4312 Guttenberg Information Technologies Center (GITC)
About Me
Marvin Nakayama is a professor in the computer science department at NJIT. He has a Ph.D. and M.S. in operations research from Stanford University, and a B.A. in mathematics-computer science from U.C. San Diego. A recipient of a CAREER award from NSF, he served as the simulation area editor for INFORMS Journal on Computing, and is on the editorial board of ACM Transactions on Modeling and Computer Simulation.
Education
Ph.D.; Stanford University; Operations Research; 1991
M.S.; Stanford University; Operations Research; 1988
B.A.; University of California-San Diego; Mathematics-Computer Science; 1986
M.S.; Stanford University; Operations Research; 1988
B.A.; University of California-San Diego; Mathematics-Computer Science; 1986
Website
2025 Spring Courses
IS 726 - INDEPENDENT STUDY II
CS 701B - MASTER'S THESIS
CS 725 - INDEPENDENT STUDY I
CS 726 - INDEPENDENT STUDY II
CS 790A - DOCT DISSERTATION & RES
IS 488 - INDEPENDENT STUDY IN INFO
CS 488 - INDEPENDENT STUDY IN CS
CS 792 - PRE-DOCTORAL RESEARCH
IS 700B - MASTER'S PROJECT
IS 776 - IS RESEARCH STUDY
IS 725 - INDEPENDENT STUDY I
IS 701B - MASTER'S THESIS
CS 700B - MASTER'S PROJECT
IS 489 - INFO UNDERGRAD THESIS RESEARCH
IS 790A - DOCT DISSERTATION & RES
IS 792 - PRE-DOCTORAL RESEARCH
CS 701B - MASTER'S THESIS
CS 725 - INDEPENDENT STUDY I
CS 726 - INDEPENDENT STUDY II
CS 790A - DOCT DISSERTATION & RES
IS 488 - INDEPENDENT STUDY IN INFO
CS 488 - INDEPENDENT STUDY IN CS
CS 792 - PRE-DOCTORAL RESEARCH
IS 700B - MASTER'S PROJECT
IS 776 - IS RESEARCH STUDY
IS 725 - INDEPENDENT STUDY I
IS 701B - MASTER'S THESIS
CS 700B - MASTER'S PROJECT
IS 489 - INFO UNDERGRAD THESIS RESEARCH
IS 790A - DOCT DISSERTATION & RES
IS 792 - PRE-DOCTORAL RESEARCH
Teaching Interests
Theory of Computation, Stochastic Simulation and Modeling
Past Courses
CS 103: COMPUT SCI-BUSINESS PROB
CS 341: FOUND OF COMPUTER SCIENCE II
CS 341: FOUNDATIONS OF COMPUTER SCIENCE II
CS 661: SYSTEMS SIMULATION
IE 651: INDUSTRIAL SYM & MODEL
CS 341: FOUND OF COMPUTER SCIENCE II
CS 341: FOUNDATIONS OF COMPUTER SCIENCE II
CS 661: SYSTEMS SIMULATION
IE 651: INDUSTRIAL SYM & MODEL
Research Interests
Stochastic modeling, Monte Carlo, randomized quasi-Monte Carlo, discrete-event simulation, variance reduction, output analysis, statistics, fault-tolerant computing, risk analysis, energy.
Journal Article
Marvin K. Nakayama, Bruno Tuffin. 2024. “Sufficient Conditions for Central Limit Theorems and Confidence Intervals for Randomized Quasi-Monte Carlo Methods.” ACM Transactions on Modeling and Computer Simulation, vol. 34, no. 3, pp. 1–38.
Yajuan K Li, Zachary T. Kaplan, Marvin K. Nakayama. 2024. “Monte Carlo Methods for Economic Capital.” INFORMS Journal on Computing, vol. 36, no. 1, pp. 266–284.
Jose Blanchet, Juan Li, Marvin K. Nakayama. 2019. “Rare-Event Simulation for Distribution Networks.” Operations Research, vol. 67, no. 5, pp. 1383–1396.
Hui Dong, Marvin K. Nakayama. 2017. “Quantile Estimation With Latin Hypercube Sampling.” Operations Research, vol. 65, no. 6, pp. 1678-1695.
Andres Alban, Hardik Darji, Atsuki Imamura, Marvin K. Nakayama. 2017. “ Efficient Monte Carlo Methods for Estimating Failure Probabilities.” Reliability Engineering and System Safety/Elsevier, vol. 165, pp. 376-394.
Yajuan K Li, Zachary T. Kaplan, Marvin K. Nakayama. 2024. “Monte Carlo Methods for Economic Capital.” INFORMS Journal on Computing, vol. 36, no. 1, pp. 266–284.
Jose Blanchet, Juan Li, Marvin K. Nakayama. 2019. “Rare-Event Simulation for Distribution Networks.” Operations Research, vol. 67, no. 5, pp. 1383–1396.
Hui Dong, Marvin K. Nakayama. 2017. “Quantile Estimation With Latin Hypercube Sampling.” Operations Research, vol. 65, no. 6, pp. 1678-1695.
Andres Alban, Hardik Darji, Atsuki Imamura, Marvin K. Nakayama. 2017. “ Efficient Monte Carlo Methods for Estimating Failure Probabilities.” Reliability Engineering and System Safety/Elsevier, vol. 165, pp. 376-394.
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Conference Paper
“Efficiency of Estimating Functions of Means in Rare-Event Contexts”
IEEE, December 2023.
“Confidence Intervals for Randomized Quasi-Monte Carlo Estimators”
IEEE, December 2023.
“Density Estimators of the Cumulative Reward up to a Hitting Time to a Rarely Visited Set of a Regenerative System ”
IEEE, December 2022.
“Sufficient Conditions for a Central Limit Theorem to Assess the Error of Randomized Quasi-Monte Carlo Methods”
IEEE, December 2021.
“Comparing Regenerative-Simulation-Based Estimators of the Distribution of the Hitting Time to a Rarely Visited Set ”
IEEE, December 2020.
IEEE, December 2023.
“Confidence Intervals for Randomized Quasi-Monte Carlo Estimators”
IEEE, December 2023.
“Density Estimators of the Cumulative Reward up to a Hitting Time to a Rarely Visited Set of a Regenerative System ”
IEEE, December 2022.
“Sufficient Conditions for a Central Limit Theorem to Assess the Error of Randomized Quasi-Monte Carlo Methods”
IEEE, December 2021.
“Comparing Regenerative-Simulation-Based Estimators of the Distribution of the Hitting Time to a Rarely Visited Set ”
IEEE, December 2020.
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Chapter
Marvin K. Nakayama, Bruno Tuffin. 2022. “Array-RQMC to Speed up the Simulation for Estimating the Hitting-Time Distribution to a Rare Set of a Regenerative System.” In Zdravko Botev, Alexander Keller, Christiane Lemieux, Bruno Tuffin (Eds.), Advances in Modeling and Simulation: Festschrift for Pierre L'Ecuyer pp. 333-352. , Switzerland: Springer, 2022.
Conference Proceeding
“A Tutorial on Quantile Estimation via Monte Carlo”
Springer Proceedings in Mathematics & Statistics, January (1st Quarter/Winter) 2020.
“Efficient Estimation of the Mean Hitting Time to a Set of a Regenerative System”
IEEE, December 2019.
“Randomized Quasi-Monte Carlo for Quantile Estimation”
IEEE, December 2019.
“On the Estimation of Mean Time to Failure by Simulation”
2017 Winter Simulation Conference, IEEE, December 2017.
“Quantile Estimation Using Conditional Monte Carlo and Latin Hypercube Sampling”
2017 Winter Simulation Conference, IEEE, December 2017.
Springer Proceedings in Mathematics & Statistics, January (1st Quarter/Winter) 2020.
“Efficient Estimation of the Mean Hitting Time to a Set of a Regenerative System”
IEEE, December 2019.
“Randomized Quasi-Monte Carlo for Quantile Estimation”
IEEE, December 2019.
“On the Estimation of Mean Time to Failure by Simulation”
2017 Winter Simulation Conference, IEEE, December 2017.
“Quantile Estimation Using Conditional Monte Carlo and Latin Hypercube Sampling”
2017 Winter Simulation Conference, IEEE, December 2017.
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Conference Abstract
“Quantile Estimation via a Combination of Conditional Monte Carlo and Latin Hypercube Sampling”
13th International Conference in Monte Carlo & Quasi-Monte Carlo Methods in Scientific Computing, INRIA, July (3rd Quarter/Summer) 2018.
13th International Conference in Monte Carlo & Quasi-Monte Carlo Methods in Scientific Computing, INRIA, July (3rd Quarter/Summer) 2018.
Other
“Efficient Monte Carlo Methods for Estimating Risk of Nuclear Power Plants”
BOOK OF ABSTRACTS Eighth International Undergraduate Summer Research Symposium, July (3rd Quarter/Summer) 2015.
“Efficient Algorithms for Analyzing Cascading Failures in a Markovian Dependability Model”
Book of Abstracts: Seventh International Summer Research Symposium, July (3rd Quarter/Summer) 2014.
BOOK OF ABSTRACTS Eighth International Undergraduate Summer Research Symposium, July (3rd Quarter/Summer) 2015.
“Efficient Algorithms for Analyzing Cascading Failures in a Markovian Dependability Model”
Book of Abstracts: Seventh International Summer Research Symposium, July (3rd Quarter/Summer) 2014.
Technical Report
“Characterization and Quantification of Safety Margin”
Argonne National Laboratory, Department of Energy,
Argonne National Laboratory, Department of Energy,