معرفی
M. Hakan Hekimoglu serves as Associate Professor of Supply Chain Management at Rensselaer Polytechnic Institute's Lally School of Management, holding the James M. Tien ’66 Dean’s Faculty Fellow appointment (2025) and directing the Lally PhD Program from his Pittsburgh 2104 office.
His academic credentials include:
- PhD in Supply Chain Management, Syracuse University
- MA in Economics, Syracuse University
- MS in Finance, Bilkent University
- BS in Industrial Engineering, Bilkent University
Dr. Hekimoglu's research pioneers interdisciplinary approaches at the supply chain-finance-analytics nexus, specializing in mathematical and empirical methodologies for disruption risk management across supply, demand, quality, price, and information uncertainties. His industry-collaborative work transforms theoretical frameworks into practical solutions for complex operational challenges.
Analysis of his 2017-2024 publications reveals dominant research trajectories in three interconnected domains: real-time disruption response systems (particularly in delivery operations), sophisticated wine market analytics integrating weather/climate variables with critic scores, and blockchain-enabled supply chain transparency. These threads consistently address uncertainty quantification through rigorous modeling published in Manufacturing & Service Operations Management, Production and Operations Management, and Decision Sciences.
His scholarly impact is recognized through:
- James M. Tien ’66 Dean’s Faculty Fellow (2025)
- Trustee Celebration of Faculty Achievement (2023, 2017)
- A. W. Lawrence Junior Development Fellowship (2020)
- MSOM iFORM Best Paper Award Finalist (2018)
- Best Published Paper Award from Lally School of Management (2016)
As Director of the Lally PhD Program, Dr. Hekimoglu mentors doctoral candidates while securing industry partnerships that fund his research. Media outlets including Forbes, Phys.org, and ABC News10 have featured his applied work on hurricane-related supply chain disruptions and wine market dynamics, demonstrating significant real-world translation of academic insights.
