Ahmadreza Marandi

Dr. Ahmadreza Marandi is a tenured Assistant Professor at Eindhoven University of Technology (TU/e), affiliated with the Operations, Planning, Accounting, and Control (OPAC) group, and an assistant professor at the Eindhoven Artificial Intelligence Systems Institute (EAISI). He holds an adjunct role at the University of British Columbia. His research focuses on data-driven robust optimization, addressing nonlinearity and uncertainty in complex systems, particularly in high-tech industries and supply chains.

Education: PhD in Operations Research from Tilburg University (2017).

Research Interests: Robust Optimization, Resilient Engineering, Convex Optimization, and applications in supply chain networks and high-tech systems. He emphasizes mathematical tools to solve real-world decision-making challenges, including inventory management, intervention planning, and adaptive treatment protocols in radiotherapy.

Key Contributions: Developed scalable optimization algorithms for interconnected infrastructure systems and robust spare parts inventory management. His work on intermediate imaging in radiotherapy planning has advanced treatment resistance management. He also co-chaired ISMP2027 and is part of the 4TU Resilience Engineering Center’s steering group.

Awards & Recognition: Co-authored a paper winning the College of Supply Chain Management’s best student paper at the 2023 Annual POMS Conference. His research has been published in top journals like *Annals of Operations Research*, *Reliability Engineering & System Safety*, and *Journal of Global Optimization*.

Advising & Collaborations: Supervises four PhD students (Sina Shahri Majarshin, Alireza Yazdani Esfidvajani, Marloes Remijnse, Zhao Kang). Collaborates with industry partners on projects like cold chain optimization and resilient supply chain design. Active in organizing academic events, including the Robust Optimization Webinar series.

Labs & Teams: Involved with EAISI High Tech Systems and the 4TU Resilience Engineering Center. His work bridges theoretical optimization with practical applications in high-tech systems and resilient infrastructure.