Research Summary
Research Summary
Overview
Description
Professor Goh’s primary research interest is applying mathematical models to real-world problems in health care in order to inform, improve, and enhance medical decision making and health policy. His recent work in this domain focuses on developing new methods for active postmarketing drug surveillance, assessing the human and economic costs of workplace stressors, and comparing the cost-effectiveness of screening strategies for colorectal cancer.
His secondary interest is developing theory for optimal decision making under uncertainty. It supports his primary research agenda by supplying a fresh source of tools and ideas that enriches his models for health care applications. Within this area, he has investigated inventory control problems in supply chains and the theory and applications of distributionally robust optimization.