Model Predictive Control (MPC) Professors and Supervisors in Netherlands

Dip Goswamiمشاهده پروفایل

دانشیار

Eindhoven University of TechnologyNetherlands

Dip Goswami is an Associate Professor in the Electronic Systems group at Eindhoven University of Technology (TU/e), focusing on embedded control systems for automotive and robotics applications. His work spans resource-aware design, multi-core predictability, and cyber-physical systems (CPS) optimization. He has co-authored over 80 conference papers, 20 journal articles, and received three best paper awards (ASP-DAC 2011, EUC 2010, ECYPS 2019). His research integrates predictable multi-core architectures distributed automotive control image-based control systems real-time optimization . Recent publications highlight advancements in nonlinear MPC for water networks DNN-driven motion control multi-rate sensor fusion parallel GPU solvers resource-constrained CPS . Scientific Awards: Best Paper Award at ECYPS 2019 Best Paper Award in ASP-DAC 2011 Best Paper Award in EUC 2010 He actively contributes to journal editorial boards (e.g., Microprocessors and Microsystems ) and serves on program committees for DAC, DATE, RTSS, and EMSOFT. Goswami's work aligns with UN SDG 4 (Quality Education) and SDG 9 (Industry Innovation), bridging control theory and embedded systems implementation.

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Dinesh Kallurمشاهده پروفایل

استادیار

Eindhoven University of TechnologyNetherlands

Dinesh Kallur is an Assistant Professor at Eindhoven University of Technology, affiliated with the Mechanical Engineering department and EAISI High Tech Systems. His research focuses on distributed optimization, numerical optimal control, and Bayesian optimization frameworks. Education: PhD in Chemical Engineering (Norwegian University of Science and Technology), MSc in Control Systems (Imperial College London) His work spans applications in fusion technology and solar energy systems. Key publications address predictive control models for tokamak devices, real-time optimization in parabolic trough plants, and Bayesian tuning of robotic controllers. Recent research output trends include: 1) predictive control strategies for fusion energy systems (2025), 2) distributed optimization frameworks for solar plants (2023-2024), and 3) Bayesian optimization approaches for shared controller systems (2024). Scientific Awards: NWO Veni Grant (2023) EuroTech Future Award (2023) Active in teaching courses on energy systems control, tokamak operations, and engineering optimization, he has contributed to 6 research outputs since 2023.

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Bart De Schutterمشاهده پروفایل

استاد

Delft University of TechnologyNetherlands

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.

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Erik Steurمشاهده پروفایل

استادیار

Eindhoven University of TechnologyNetherlands

Erik Steur is an Assistant Professor at the Department of Mechanical Engineering at Eindhoven University of Technology (TU/e). He holds roles as a Core member of the ICMS (Institute for Complex Molecular Systems) and Foundational member of EAISI (Eindhoven Artificial Intelligence Systems Institute). His research focuses on collective dynamics in networked systems, cluster synchronization, pattern generation, and chemical reaction network modeling. He has held positions at TU/e, Delft University of Technology, and KU Leuven, contributing to academic leadership in areas like the 'Grip on Complexity' pillar. Education: M.Sc. (cum laude) in Mechanical Engineering, TU/e (2007) Ph.D. in Mechanical Engineering, TU/e (2011) Research Interests: Steur’s work spans nonlinear systems, control theory, and synchronization phenomena. His projects integrate experimental and computational methods, with applications in microfluidics, neuromorphic systems, and energy networks. Recent studies include artificial cilia-driven fluid mixing and synchronization in time-delayed coupled systems. Articles Trends: Recent publications emphasize synchronization in networked systems, biomimetic actuators, and energy management. Key topics include magnetic artificial cilia for fluid transport, distributed control strategies, and hybrid neuromorphic controllers. Achievements: He serves as an Associate Editor for Systems and Control Letters and advises Communications in Nonlinear Science . Supervised 24 academic works, contributing to TU/e’s educational programs in networked systems and dynamics. Labs/Teams: Active in TU/e’s Mechanical Engineering labs, leading ICMS initiatives on complex systems and collaborating internationally on control systems research.

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George Papafotiouمشاهده پروفایل

استاد

Eindhoven University of TechnologyNetherlands

George Papafotiou is a Full Professor in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e) and Head of the Power Electronics Lab. His research focuses on computational intelligence, particularly Model Predictive Control (MPC), applied to power electronics systems for applications in renewable energy, high-efficiency power conversion, and grid integration. He holds affiliations with the EIRES Research Institute and the Cyber-Physical Systems Center in Eindhoven. Academic Background: Papafotiou earned his PhD in Electrical Engineering from Aristotle University of Thessaloniki (2002) and completed a postdoc at ETH Zurich (Switzerland). He spent 15 years at ABB in roles including Scientist, Global R&D Manager for SW/Control HW, and Quality Manager, leading projects on MPC-based control systems for industrial drives and energy management. Research Interests: His work centers on advancing power electronics through MPC for microsecond-scale control, enabling reliable systems critical to a carbon-free future. Key areas include modular multilevel converters (MMCs), soft-switching techniques, grid-tied power electronics, and harmonics mitigation in high-voltage systems. Projects: Current projects include RelSST: Developing reliable solid-state transformers for smart grids. HiVECAF: Designing versatile, efficient active filters for power quality improvement. Teaching: He teaches Electric Circuits Analysis for Energy Conversion Electric Drive Systems Grants & Labs: Leads the Power Electronics Lab, focusing on applied research in sustainable energy systems and industrial automation.

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Mircea Lazarمشاهده پروفایل

دانشیار

Eindhoven University of TechnologyNetherlands

Mircea Lazar is an Associate Professor in the Control Systems group at Eindhoven University of Technology. His research spans constrained control, model predictive control (MPC), and stability analysis of hybrid systems, with applications in power systems, smart grids, and precision mechatronics. Research highlights include: Development of data-driven predictive control methods Stability guarantees for nonlinear and hybrid systems Applications in water networks, power converters, and mechatronics He has received the EECI PhD Award and NWO VENI grant. Recent publications focus on real-time MPC implementations, physics-guided neural networks, and optimization for large-scale systems. Collaborations include ASML, DAF, Philips, and Ford. He chairs the IEEE CSS Technical Committee on Hybrid Systems and has supervised 9 PhD students.

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Christina Papadimitriouمشاهده پروفایل

استادیار

Eindhoven University of TechnologyNetherlands

Christina Papadimitriou is an Assistant Professor in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e), affiliated with the Intelligent Energy Systems and Electrical Energy Systems research groups. Her work focuses on smart grid operation, integrated energy systems, and grid flexibility for decarbonization. PhD and Diploma in Electrical & Computer Engineering from University of Patras Senior Researcher at National Technical University of Athens (2012-2016) System Engineer at Hellenic Distribution Network Operator (2016-2019) Special Scientist at University of Cyprus (2019-2021) Her research explores: Smart grid resilience through active asset flexibility Demand-side optimization in integrated grids Power-to-X (PtX) technology operation models Energy hub coordination with logistics fleets Multi-energy carrier synergies in residential clusters Recent work demonstrates: Grid capacity enhancement via dynamic charging strategies (IEEE Access 2024) Multi-objective PtX optimization tools (CRC Press 2025) Smart grid maturity assessment frameworks (Electric Power Systems Research 2024) She coordinates the eNeuron project under Horizon2020 and serves as peer reviewer for multiple journals.

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Mauro Salazarمشاهده پروفایل

استادیار

Eindhoven University of TechnologyNetherlands

Mauro Salazar is an Assistant Professor in the Control Systems Technology section of the Department of Mechanical Engineering at Eindhoven University of Technology (TU/e), with co-affiliations at the Eindhoven AI Systems Institute (EAISI) in both Health and Mobility domains. He leads his own research group focused on optimization models and methods for systems and control. His educational background includes: B.Sc. and M.Sc. in Mechanical Engineering from ETH Zürich (2012, 2015) Master thesis conducted at EPFL's Automatic Control Lab Ph.D. in Mechanical Engineering from ETH Zürich (2019) in collaboration with Ferrari Formula 1 Postdoctoral Scholar at Stanford University's Autonomous Systems Lab (2019-2020) Salazar's research centers on optimization models for multi-scale cyber-socio-technical systems with applications spanning mobility systems, pandemic response, and material design. His work bridges theoretical optimization with practical implementation, particularly in sustainable mobility solutions where he develops methods for optimal design and operation of transportation systems from single vehicles to entire networks. He investigates mesoscopic user behavior modeling and designs incentive schemes to align individual and system-level objectives in transportation networks. His recent publications (2025) demonstrate a strong focus on sustainable mobility systems, with recurring themes in electric vehicle fleet management, battery degradation modeling, ride-pooling algorithms, and energy management for transportation electrification. His work spans multiple disciplines including automotive engineering, control systems, energy management, and public health, characterized by rigorous mathematical optimization approaches applied to real-world challenges. His scientific recognitions include: Two ETH Medals (for Master's and PhD theses) Best Student Paper awards at ITS 2018 and ECC 2022 Best Teacher Award (2021) Nomination for TU/e Young Researcher Award (2022) Salazar actively advises research projects and secured funding through the Dutch Research Council's NEON project (Crossover research program, Grant 17628). His teaching portfolio includes Optimal Control and Reinforcement Learning, Engineering Optimization, and Advanced Full-Electric and Hybrid Powertrain Design. He leads the 'Group Salazar' within the Control Systems Technology section and contributes to EAISI Health and Mobility initiatives.

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