Modeling and Simulation with Digital Engineering

SEOR research in modeling and simulation with digital engineering focuses on the development of high-fidelity mathematical representations and computational tools to predict and enhance the performance of complex environments. 

Faculty leverage simulation optimization, systems science, and digital twin technology to analyze system-level behaviors and prepare for critical rare-event scenarios. Building on this work, research emphasizes targeted applications of systems science and modeling to support decision-making in complex environments.

Key areas include cost and systems modeling, probabilistic approaches for stochastic analysis, and the application of systems thinking to sociotechnical systems. Faculty also examine network-of-networks systems with a focus on human performance, safety, and risk, and apply queueing theory and simulation methods to better understand uncertainty and rare, high-impact events.

A close-up of a financial chart with trend lines and volume indicators representing data-driven modeling and analysis.
Support Risk and Reliability Analysis

Specialize in Stochastic Models (STM) in your MS in Operations Research and gain the skills to address uncertainty, randomness, and variability using probability and random processes.