Seong-Hee Kim

Professor


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Education

  • Ph.D. Industrial Engineering and Management Science (2001), Northwestern University
  • M.S. Industrial Engineering and Management Science (1998), Northwestern University
  • B.S. Industrial Management (1997), Korea Advanced Institute of Science and Technology

Expertise

  • Simulation
  • Simulation Optimization
  • Manufacturing Applications
  • Data Science and Machine Learning

About

Seong-Hee Kim is a Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. She held the Coca Cola Professorship from 2014 to 2017 and is currently on leave serving as Executive Vice President at Samsung SDI, where she leads a research team developing simulation-based and data-driven methodologies for battery systems. 

Dr. Kim received a B.S. in Industrial Management from Korea Advanced Institute of Science and Technology (KAIST) and an M.S. & Ph.D. in Industrial Engineering and Management Sciences from Northwestern University. 

Research

Dr. Kim's research interest centers on data-based decision making, simulation optimization for stochastic simulation, statistical output analysis, quality control, and applications of simulation methods to manufacturing -- with a particular focus on environmental management, shipbuilding, and rechargeable battery systems. She builds methods that are not only theoretically sound but transferable across systems and domains. This philosophy is reflected in her applied work in shipbuilding and rechargeable battery manufacturing. 

Currently on leave at Samsung SDI as Executive Vice President, Dr. Kim leads a team applying methodologies in an industrial setting, encompassing deep learning-based image classification, early risk detection via machine learning and deep learning, and computational optimization for battery materials design. This experience continues to enrich her academic research agenda.  

Teaching

Dr. Kim's teaching philosophy centers on building rigorous mathematical foundations while connecting theory to real-world impact. She teaches simulation, probability/statistics, stochastic processes, and simulation optimization at both undergraduate and graduate levels. Several algorithms developed by Dr. Kim and her collaborators have been incorporated into widely used commercial simulation software packages --- including KN in Simio, the Process Analyzer in Arena, and Rank and Select in OptQuest --- tools that are broadly adopted in both academic curricula and industrial practice.

Awards and Honors

  • Northwestern IEMS Alumni Award
  • The Harold W. Kuhn Award
  • Class of 1934 Course Survey Teaching Effectiveness Award
  • CAREER Award, National Science Foundation
  • INFORMS Simulation Society Outstanding Simulation Publication Award

Representative Publications

  • Zhou, Y., S. Andradottir, and S.-H. Kim. Selection of the Best in the Presence of Subjective Stochastic Constraints, ACM TOMACS, accepted.
  • Zhou, Y., S. Andradottir, S.-H. Kim, and C. Park. 2024. Pruning Inferior Systems Using Subjective Constraints with Sequentially Added Thresholds, Sequential Analysis, accepted.
  • He, J., S.-I. Hong and S.-H. Kim. Spatiotemporal Planning for Block Assembly in Shipbuilding, Journal of Scheduling, accepted.
  • Gong, T., D. Liu, H. Kim, S.-H. Kim, T. Kim, D. Lee, and Y. Xie. Distribution-free Image Monitoring with Application to Battery Coating Process, IISE Transactions, accepted.
  • Chen, J., M.M. Aral, S.-H. Kim, C. Park, and Y. Xie. 2023. Constrained Bayesian Optimization and Spatio-Temporal Surveillance for Sensor Network Design in the Presence of Measurement Errors, Engineering Optimization, 55(3):510-525.
  • Zhou, Y., S. Andradottir, and S.-H. Kim. 2022. Finding Feasible Systems for Subjective Constraints Using Recycled Observations, INFORMS Journal on Computing, 34(6):2867-3350.
  • Park, C., and S.-H. Kim. 2015. Penalty Function with Memory for Discrete Optimization via Simulation with Stochastic Constraints, Operations Research, 63(5):1195 – 1212.
  • Andradottir, S. and S.-H. Kim. 2010. Fully Sequential Procedures for Comparing Constrained Systems via Simulation, Naval Research Logistics, 57(5):403-421
    KUHN Award Winning Paper – “the most highly cited paper (measured in citations per year) published in Naval Research Logistics during the 2010-2012 time period.”
  • Kim, S.-H., C. Alexopoulos, K.-L. Tsui, and J. R. Wilson. 2007. A Distribution-Free Tabular CUSUM Chart for Autocorrelated Data , IIE Transactions, 39:317-330
    Online Supplement to “A Distribution-Free Tabular CUSUM Chart for Autocorrelated Data” , 2006
    One of the 10 most-cited articles published in Year 2005 – 2009 in IIE Transactions (cited by Taylor & Francis in 2010)
  • Boesel, J., B. L. Nelson, and S.-H. Kim. 2003. Using Ranking and Selection to “Clean Up” After Simulation Optimization, Operations Research, 51:814-825
    INFORMS Simulation Society Outstanding Simulation Publication Award winning paper
  • Goldsman, D., S.-H. Kim, W. Marshall, and B. L. Nelson. 2002. Ranking and Selection Procedures for Steady-State Simulation: Procedures and Perspectives, Informs Journal on Computing, 14:2-19
  • Kim, S.-H. and B. L. Nelson. 2001. A Fully Sequential Procedure for Indifference-Zone Selection in Simulation, ACM TOMACS, 11:251-273