Bart De Schutter is a Full Professor and Head of the Delft Center for Systems and Control (DCSC) at Delft University of Technology , The Netherlands. He leads a research group focused on advanced control methodologies with applications in transportation, energy, and environmental systems. His research interests span model predictive control (MPC) , hybrid and piecewise-affine systems , multi-agent and distributed control , reinforcement learning , and discrete event systems with applications in intelligent transportation, smart grids, and underwater robotics. His work integrates model-based and data-driven approaches to enable robust, scalable, and intelligent control of large-scale networks. His recent publications reflect a strong trend toward integrating learning with formal control methods, ensuring safety and performance in complex hybrid systems. Research themes include learning-based MPC, scenario reduction for stochastic control, stability analysis of max-plus systems, and applications in railway scheduling and marine monitoring. Notable scientific awards include: ERC Advanced Grant (CLariNet, 2021–2026) Richard C. DiPrima Prize for PhD thesis Robert Stock Prize for PhD theses in Exact Sciences VIDI grant from STW IEEE Fellow IFAC Fellow Bart De Schutter has coordinated major EU projects such as HD-MPC , SeaClear , and SeaClear2.0 , demonstrating leadership in both theoretical innovation and real-world applications. He serves as a senior editor for IEEE Transactions on Intelligent Transportation Systems and associate editor for IEEE Transactions on Automatic Control . He leads a research team working on next-generation control solutions for autonomous systems and infrastructure, with ongoing projects in intelligent traffic control, smart energy systems, and underwater robotics. The group actively recruits PhD and postdoctoral researchers, indicating a vibrant and expanding lab environment.









