Eunshin Byon smiles and poses for a portrait.

Eunshin Byon

Associate Professor


2773 IOE


Additional Title(s)

  • IOE Diversity Ally

Dr. Byon’s research interests include reliability evaluation, fault diagnosis/condition monitoring, predictive modeling and data analytics, and operations and maintenance decision-making for stochastic systems. Her recent research focuses on uncertainty quantification of stochastic systems using stochastic simulations, reliability analysis and improvement of large-scale, interconnected systems with applications to renewable power power systems and manufacturing processes. She is a member of IIE, INFORMS, and IEEE.


Research Interests

  • Analytics
    Predictive Data Analytics
  • Applications
  • Risk Management
  • Industrial Operations
    Operations & Maintenance Optimization
  • Operations Research Tools
    Stochastic Opt. & Control
  • Quality & Applied Statistics
    Bayesian Statistics
    Design of Experiments
    Fault Diagnosis & Condition Monitoring
    Reliability & Maintainability
    Statistical Quality Control

Research areas:
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Professional Service



  • Byon, E., Choe, Y., Yampikulsakul N., Adaptive modeling and prediction in time-variant processes with application to wind power systems, to appear in IEEE Transactions on Automations Science and Engineering.
  • Choe, Y., Byon, E., and Chen, N., 2015, Importance sampling for the reliability evaluation with stochastic simulation models, Technometrics, Vol. 57, No. 3, pp. 351-361.
  • Ko. Y and Byon, E., Reliability analysis of large-scale systems with identical units, 2015, IEEE Transactions on Reliability, Vol. 64, No. 1, pp. 420-434.
  • Yampikulsakul N., Byon, E., Huang S., Sheng S. and You M.*, 2014, Condition monitoring of wind turbine system with nonparametric regression-based analysis, IEEE Transactions on Energy Conversion, Vol. 29, No. 2, pp. 288-299.
  • Byon, E., 2013, Wind turbine operations and maintenance: A tractable approximation of dynamic decision-making, IIE Transactions, Vol. 45, No. 11, pp. 1188-1201
  • Lee, G., Byon, E., Ntaimo, L., and Ding. Y, 2013, Bayesian spline method for assessing extreme loads on wind turbines, Annals of Applied Statistics, Vol. 7, No. 4, pp. 2034–2061
  • Byon, E., Shrivastava, A. K., and Ding, Y., 2010, A classification procedure for highly imbalanced class sizes, IIE Transactions, Vol. 42, No. 4, pp. 288-303
  • Byon, E., Ding, Y. and Ntaimo, L., 2010, Optimal maintenance strategies of wind turbine systems under stochastic weather conditions, IEEE Transactions on Reliability, Vol. 59, No. 2, pp. 393-404.