Christos Alexopoulos

About

Christos Alexopoulos is the Associate Chair for Graduate Studies, Kiplinger Faculty Fellow, and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. His research interests center on applied probability, simulation analysis methodology, statistics, and optimization under uncertainty. His recent work involves the design and implementation of efficient sequential methods for estimating measures of risk and error in simulation experiments, as well as the optimization of production and inventory systems using machine learning methods. Dr. Alexopoulos has been a core contributor to simulation education in ISyE since 1988. In 1999, he co-founded the cross-disciplinary Modeling & Simulation Research & Education Center, which served as a springboard for the creation of the School of Computational Science and Engineering. He has served as the unit coordinator for the graduate programs in CSE since their inception. In addition to his instructional contributions, he has co-developed instructional games and the Sequest Software for estimating measures of statistical risk and error. His work has been recognized with awards such as the Best Paper Award at the 24th ACM/IEEE/SCS Workshop on Principles of Advanced and Distributed Simulation in 2010, the Best Paper Award in Operations Engineering and Analysis of IIE Transactions in 2010, and the INFORMS Simulation Society Outstanding Simulation Publication Award in 2007.

Research topics

• Computer Science
• Applied mathematics
• Mathematics
• Statistics
• Algorithm

Selected publications

• Steady-State Quantile Estimation Using Standardized Time Series

  2018 Winter Simulation Conference (WSC) · 2020 · 8 citations

  1st authorCorresponding

  Extending developments of Calvin and Nakayama in 2013 and Alexopoulos et al. in 2019, we formulate point and confidence-interval (CI) estimators for given quantiles of a steady-state simulation output process based on the method of standardized time series (STS). Under mild, empirically verifiable conditions, including a geometric-moment contraction (GMC) condition and a functional central limit theorem for an associated indicator process, we establish basic asymptotic properties of the STS quan…

  PublisherDOI

• Geometric-Moment Contraction of G/G/1 Waiting Times

  Springer eBooks · 2022 · 7 citations

  PublisherDOI

• Confidence Intervals and Regions for Quantiles using Conditional Monte Carlo and Generalized Likelihood Ratios

  2018 Winter Simulation Conference (WSC) · 2020 · 5 citations

  This article develops confidence intervals (CIs) and confidence regions (CRs) for quantiles based on independent realizations of a simulation response. The methodology uses a combination of conditional Monte Carlo (CMC) and the generalized likelihood ratio (GLR) method. While batching and sectioning methods partition the sample into nonoverlapping batches, and construct CIs and CRs by estimating the asymptotic variance using sample quantiles from each batch, the proposed techniques directly esti…

  PublisherDOI

• Deep Reinforcement Learning for Large-Scale Inventory Management

  SSRN Electronic Journal · 2023-01-01 · 3 citations

  articleOpen access
  PublisherDOI

• A Sequential Method for Estimating Steady-State Quantiles Using Standardized Time Series

  2022 Winter Simulation Conference (WSC) · 2022-12-11 · 3 citations

  article

  We propose SQSTS, an automated sequential procedure for computing confidence intervals (CIs) for steady-state quantiles based on Standardized Time Series (STS) processes computed from sample quantiles. We estimate the variance parameter associated with a given quantile estimator using the order statistics of the full sample and a combination of variance-parameter estimators based on the theoretical framework developed by Alexopoulos et al. in 2022. SQSTS is structurally less complicated than its…

  PublisherDOI

Recent grants

• Collaborative Research: Effective Sequential Procedures for Risk and Error Estimation in Steady-state Simulation

  NSF · $234k · 2012–2016

Frequent coauthors

• David Goldsman

  Georgia Institute of Technology

  66 shared

• James R. Wilson

  North Carolina State University

  44 shared

• Anup C. Mokashi

  Memorial Sloan Kettering Cancer Center

  14 shared

• Kemal Dinçer Dingeç

  Gebze Technical University

  10 shared

• Nilay Tanık Argon

  University of North Carolina at Chapel Hill

  8 shared

• Melike Meterelliyoz

  8 shared

• Seong‐Hee Kim

  Sungkyunkwan University

  7 shared

• Tûba Aktaran‐Kalaycı

  AT&T (United States)

  7 shared

Education

• PhD, Operations Research

  University of North Carolina System

  1988

• BS, Mathematics

  Aristotle University of Thessaloniki

  1982

Awards & honors

• Best Paper Award, 24th ACM/IEEE/SCS Workshop on Principles o…
• Best Paper Award in Operations Engineering and Analysis of I…
• INFORMS Simulation Society Outstanding Simulation Publicatio…
• Honorable Mention in IIE Transactions Focused Issue on Opera…
• Winner of Best Paper Award at 24th ACM/IEEE/SCS Workshop on…

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