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

2025 Fall Courses
IS 726 - INDEPENDENT STUDY II

IT 488 - INDEPENDENT STUDY

CS 701B - MASTER'S THESIS

CS 725 - INDEPENDENT STUDY I

CS 726 - INDEPENDENT STUDY II

CS 790A - DOCT DISSERTATION & RES

CS 341 - FOUND OF COMPUTER SCIENCE II

IS 488 - INDEPENDENT STUDY IN INFO

CS 488 - INDEPENDENT STUDY IN CS

CS 489 - COMPUTER SCIENCE RESEARCH PROJ

IS 491 - SENIOR PROJECT - IS

CS 792 - PRE-DOCTORAL RESEARCH

IS 700B - MASTER'S PROJECT

IS 776 - IS RESEARCH STUDY

CS 341 - FOUND OF COMPUTER SCIENCE II-HONORS

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

Research Interests
Stochastic modeling, Monte Carlo, randomized quasi-Monte Carlo, discrete-event simulation, variance reduction, output analysis, statistics, fault-tolerant computing, risk analysis, energy.
Conference Paper
"Some Asymptotic Regimes for Quantile Estimation"
IEEE, December, 2024.

"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.

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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.

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Chapter
Marvin K. Nakayama, Bruno Tuffin. "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. 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.

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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.

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.

Technical Report
"Characterization and Quantification of Safety Margin"
Argonne National Laboratory, Department of Energy.