Operations Research research is supported by premier faculty and advanced analytical and computational methods focused on optimizing complex systems under uncertainty. These efforts are driven by the need to improve efficiency, reliability, and performance in large-scale engineered systems across sectors including energy, healthcare, transportation, supply chains, and communication networks. The work emphasizes mathematical modeling, stochastic analysis, and algorithm development to support better decision-making in systems characterized by uncertainty, interdependence, and scale. Faculty develop rigorous methods grounded in probability, optimization, and system theory to improve operational performance and resource utilization.
Collectively, these efforts enable improved system efficiency, reduced risk, optimized resource allocation, and more reliable performance in complex and data-driven environments.
Stochastic Optimization
Queueing Theory
Risk Analysis
Optimization Techniques