(734) 764-6565

Applications:
Civic Infrastructure, Complex Systems, Energy Research, Environmental Sciences, Healthcare Management and Outcomes, Medical Informatics, Operations Research, Sensors and Sensor Networks
Methodologies:
Bayesian Methods, Causal Inference, Classification, Data Mining, Decision Science, Heterogeneous Data Integration, High-Dimensional Data Analysis, Machine Learning, Optimization, Predictive Modeling, Spatio-Temporal Data Analysis, Statistical Inference, Statistical Modeling, Time Series Analysis

Eunshin Byon

Associate Professor

Industrial and Operations Engineering, College of Engineering
Civil and Environmental Engineering, College of Engineering

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.