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Golman is a Postdoctoral Fellow in Freight Transport and Logistics within the Operations, Planning, Accounting and Control (OPAC) group at the Department of Industrial Engineering and Innovation Sciences at Eindhoven University of Technology (黑料福利网) in the Netherlands. She holds two Master鈥檚 degrees, both awarded cum laude: one in Industrial Engineering and one in Transport Systems Engineering. She earned her PhD in Transport and Infrastructure, also conferred cum laude in recognition of academic excellence.

Her doctoral dissertation, titled 鈥淕reen Vehicle Routing and Logistics Optimization: IoT-Driven Solutions for Modern Urban Challenges,鈥� explored how Internet of Things (IoT) technologies, in combination with advanced optimization methods, can improve the sustainability, efficiency, and resilience of urban freight systems.

Golman鈥檚 research addresses complex challenges in freight transport and logistics using methodologies from Operations Research and Artificial Intelligence. Her work involves the development of models such as integer programming, branch and price, machine learning, and reinforcement learning to optimize supply chains, increase transportation efficiency, and enhance the performance of logistics networks. These efforts are frequently conducted in collaboration with industry partners to ensure both academic rigor and real-world relevance.

Golman has authored or co-authored more than ten peer-reviewed journal articles. Her work has received over 300 citations and she holds an h-index of 8 according to Google Scholar. Her publications appear in high-impact journals including Renewable and Sustainable Energy Reviews and the Journal of Cleaner Production.

A recent recognition includes her team鈥檚 selection as a finalist in the TSL Meituan 2024 Data-Driven Research Challenge. The team鈥檚 algorithm was praised for its technical sophistication and practical applicability and will be presented at the INFORMS Annual Meeting 2025 in Atlanta