Eunhye Song

Harold and Inge Marcus Early Career Assistant Professor

Industrial and Manufacturing Engineering

Penn State University

CONTACT

Email: eus358 at psu.edu

Office: 310 Leonhard Building, University Park, PA 16802

Full CV [Download]

EDUCATION

Ph.D. in Industrial Engineering and Management Sciences, Northwestern University, 2017

M.S. in Industrial and Systems Engineering, KAIST, 2012

B.S. in Industrial and Systems Engineering, KAIST, 2010

RESEARCH INTEREST

My research interests lie in simulation analysis theory, in particular

  • Simulation optimization under model risk
  • Uncertainty quantification and sensitivity analysis of a simulation model
  • Gaussian Markov random fields-based large-scale discrete simulation optimization

PUBLICATIONS

Journal articles

Eunhye Song and Barry L. Nelson (2019) Input-Output Uncertainty Comparisons for Optimization via Simulation, Operations Research, 67(2), 562-576.

Peter Salmi, Eunhye Song, Barry L. Nelson, and Jeremy Staum (2019) Gaussian Markov Random Fields for Discrete Optimization via Simulation: Framework and Algorithms, Operations Research, 67 (1), 250-266.

Eunhye Song, Barry L. Nelson, and Jeremy Staum (2016) Shapley Effects for Global Sensitivity Analysis: Theory and Computation, SIAM/ASA Journal on Uncertainty Quantification 4 (1), 1060-1083.

Yujing Lin, Eunhye Song, and Barry L. Nelson (2015) Single-Experiment Input Uncertainty, Journal of Simulation 9, 249-259.

Eunhye Song and Barry L. Nelson (2015) Quickly Assessing Contributions to Input Uncertainty, IIE Transactions 47(9), 893-909.

Eunhye Song, B. Park and B. K. Choi (2012) Event Graph Modeling of a Homogeneous Job Shop with Bi-inline Cells, Simulation Modeling Practice and Theory 20, 1-11.

Book chapters

Eunhye Song and Barry L. Nelson (2017) Input Model Risk. In Tolk, Fowler, Shao and Yücesan (Eds.), Advances in Modeling and Simulation: Seminal Research from 50 Years of Winter Simulation Conferences (pp. 63-80), Springer, NY.

Refereed proceedings

Michael Hoffman, Eunhye Song, Michael Brundage, and Soundar Kumara (2018) Condition-based maintenance policy optimization using genetic algorithms and Gaussian Markov improvement algorithm, In Proceedings of the Annual Conference of the PHM Society 2018

Russell R. Barton, Henry Lam, and Eunhye Song (2018) Revisiting Direct Bootstrap Resampling for Input Model Uncertainty, In Proceedings of the 2018 Winter Simulation Conference, Gothenberg, Sweden.

Eunhye Song and Yi Dong (2018) Generalized Method of Moments Approach to Hyperparameter Estimation for Gaussian Markov Random Fields, In Proceedings of the 2018 Winter Simulation Conference, Gothenberg, Sweden.

Mark Semelhago, Barry L. Nelson, Andreas Waechter, and Eunhye Song (2017) Computation Methods for Simulation Optimization Using Gaussian Markov Random Fields, In Proceedings of the 2017 Winter Simulation Conference, Las Vegas, NV.

Eunhye Song (2016) Input-output Uncertainty Comparisons for Optimization via Simulation, Doctoral Colloquium, In Proceedings of the 2016 Winter Simulation Conference, Arlington, VA.

Eunhye Song, Barry L. Nelson, and L. Jeff Hong (2015) Input Uncertainty and Indifference Zone Ranking and Selection, In Proceedings of the 2015 Winter Simulation Conference, 414-424.

Eunhye Song, Barry L. Nelson, and C. D. Pegden (2014) Input Uncertainty Quantification: Advanced Tutorial, In Proceedings of the 2014 Winter Simulation Conference, 162-176.

Eunhye Song and Barry L. Nelson (2013) A Quicker Assessment of Input Uncertainty, In Proceedings of the 2013 Winter Simulation Conference, 474-485.

Eunhye Song, S. Gu, T. Choi and B. K. Choi (2011) A Framework for Integrated Simulation of Production and Material Handling Systems of TFT-LCD Fab, In Proceedings of the 2011 Summer Computer Simulation Conference, IEEE, Hague, 48-54.


PRESENTATIONS

Eunhye Song (2018) Sequential Inferential Optimization via Simulation Under Input Model Risk, INFORMS Annual Meeting 2018, Phoenix, AZ.

Eunhye Song, Mark Semelhago, Barry L. Nelson, and Andreas Waechter (2017) Computation Methods for Simulation Optimization Using Gaussian Markov Random Fields, INFORMS Annual Meeting 2017, Houston, TX.

Eunhye Song and Barry L. Nelson (2016) Leveraging the Common Input Data in Comparisons of Systems under Input Uncertainty, INFORMS Annual Meeting 2016, Nashville, TN.

Eunhye Song, Barry L. Nelson, and Jeremy Staum (2016) Multi-resolution Gaussian Markov Random Fields for Discrete Optimization via Simulation, INFORMS Annual Meeting 2016, Nashville, TN.

Eunhye Song, Barry L. Nelson, and Jeremy Staum (2014) A New Measure in Global Sensitivity Analysis: Shapley Values of Input Parameters, INFORMS Annual Meeting 2014, San Francisco, CA.

Eunhye Song, S. Gu, and B. K. Choi (2010) Event Graph Modeling of Electronics Fab with Uni-inline Cells. The 2010 Spring Joint Conference of KIIE and KORMS, Jeju, 2010.

TEACHING & ADVISING

Penn State University

  • IE 322, Probabilistic Models for Industrial Engineers, Fall 2017, 2018
  • IE 522, Discrete Event Systems Simulation, Spring 2018, 2019
  • INFORMS Student Chapter advisor, 2017 - current

Northwestern University

  • IEMS 317, Discrete-Event Systems Simulation, Spring 2015

INDUSTRY COLLABORATIONS

General Motors, Operations Research group at the R&D center

Uncertainty quantification in Content Optimization simulation at GM

Simio

Developing sample size error & sensitivity analysis module in Simio simulation software package

SOFTWARE

'shapleyPermEx' and 'shapleyPermRand' implement the Shapley effect estimation algorithm in Song, Nelson, and Staum (2016).

  • Fire spread model implemented in R for global sensitivity analysis: FireFunction.R

Used as a test function for Shapley effect analysis in Song, Nelson, and Staum (2016).

LINKS