Berk Görgülü

Overview

Dr. Berk Görgülü’s research focuses on constructing data-driven, realistic models of healthcare operations and developing predictive and prescriptive analytics to support decision-making under uncertainty. His research methodologies include stochastic modeling and optimization, queueing theory, interpretable machine learning, and Markov decision processes. While his primary work spans areas such as patient flow optimization, disease testing strategies, breast cancer screening, and kidney transplantation, Dr.Görgülü is also interested in how these challenges intersect with aging populations. In particular, his work on optimizing patient flow in rehabilitation and geriatric care units has direct implications for older adults, and he is interested in exploring how data-driven decision-making can improve healthcare outcomes for aging individuals.

Affiliations

• Member, McMaster Institute for Research on Aging (MIRA), McMaster University
• Assistant Professor, Operations Management, DeGroote School of Business
• Member, School of Computational Science and Engineering
• Member, Canadian Operational Research Society (CORS)
• Member, Institute for Operations Research and the Management Sciences (INFORMS)

Education

• BSc, Bogazici University
• MSc, Bogazici University
• PhD, University of Toronto