Susan Hunter

Susan Hunter is an Associate Professor in the Edwardson School of Industrial Engineering at Purdue University, West Lafayette, with her office located in GRIS 272. She can be contacted via email at susanhunter@purdue.edu.

Her research centers on Operations Research with deep specialization in Stochastic Optimization and Multi-objective Optimization. She develops theoretical frameworks and practical algorithms for simulation-based optimization under uncertainty, focusing on Pareto front approximation, adaptive sampling techniques, and parallel computing implementations. Key contributions include error quantification methods, confidence region constructions, and performance indicator analyses for stochastic multi-objective problems.

Analysis of her 2020-2025 publications reveals dominant trends in multi-objective stochastic simulation optimization, particularly addressing computationally expensive functions and integer-variable constraints. Her work bridges theoretical rigor (e.g., Central Limit Theorems for confidence regions) with practical tools like the SCORE algorithm for sampling allocation and bi-PASS for parallel optimization. She also contributes methodological guidance through LaTeX submission templates for academic publishing.