Find Academic Supervisors

• Public Transportation Optimization
• Electric Vehicle Scheduling
• Operations Research
• +3 more

Dr. Marcel van Kooten Niekerk serves as an Assistant Professor in the Department of Information and Computing Sciences within the Faculty of Science at Utrecht University. His academic appointment focuses on the Simulation of Complex Systems subgroup, where he applies computational methods to solve challenging transportation problems. He also maintains a professional connection with the transportation industry as a Consultant Logistics and Innovation at Qbuzz BV, demonstrating his commitment to bridging academic research with practical applications in public transport. Van Kooten Niekerk's research spans two primary domains: transportation optimization and theoretical computer science. His more recent work centers on public transportation systems, particularly focusing on the integration of electric vehicles into existing public transit networks. His expertise encompasses complex scheduling challenges including electric bus operations, platform assignments across multiple stations, and the integration of timetabling with vehicle scheduling. Earlier in his career, he made significant contributions to theoretical computer science, particularly in graph theory and combinatorial optimization problems such as partitioning graphs into triangles. His publication record reveals a clear evolution from theoretical computer science toward applied transportation research, with a growing emphasis on sustainability. The most recent publications demonstrate sophisticated approaches to handling uncertainty in electric bus operations, optimizing platform assignments across multiple bus stations in Utrecht, and developing comprehensive frameworks for reliable and sustainable public transport systems. His work consistently applies operations research methodologies, particularly integer linear programming and stochastic optimization techniques, to solve real-world transportation challenges. Van Kooten Niekerk has established himself as a researcher who effectively bridges theoretical computer science with practical transportation applications. His work has gained significant attention, with some publications accumulating over 100 citations and reader captures, indicating substantial impact in the transportation research community. His doctoral thesis on optimizing for reliable and sustainable public transport represents a comprehensive contribution to the field of electric vehicle integration in public transportation systems.

Vladimir FilipovićView profile

Professor

• Operational research
• Computational intelligence
• Big data
• +5 more

Vladimir Filipović is a Full Professor at the Department for Computer Science, Faculty of Mathematics, University of Belgrade. He is also a member of the Modelling and optimization group within the Department for Computer Science. His academic career spans over 30 years at the University of Belgrade, where he has held various positions including teaching assistant, assistant professor, associate professor, and since December 2019, Full Professor. He has also served in administrative roles such as Head of the Software Examination and Certification Laboratory (2007-2016), Vice Dean for Academic Affairs (2008-2011), and Head of the Department for Computer Science (2017). Additionally, he was a Visiting Fellow at University Milano-Bicocca (2017-2018) and a visiting professor at University of Banja Luka (2007-2020). Dr. Filipović earned his BSc in Computer Science (1993), MSc degree (1998), and PhD in Computer Science (2006), all from the Faculty of Mathematics, University of Belgrade. His doctoral thesis was titled 'Selection and Migration Operators and Web Services in Evolutionary Applications'. His research interests span across Operational research, Computational intelligence, Big data, Soft-computing, Metaheuristics, Evolutionary algorithms, Bioinformatics, and Graph theory. His work demonstrates a strong interdisciplinary approach, bridging theoretical computer science with practical applications in bioinformatics, network optimization, and biomedical data analysis. His research has resulted in numerous publications in high-impact journals and conferences, with a recent focus on topological variable neighborhood search methods and cancer evolution inference. Analysis of his recent publications (2020-2024) reveals a strong trend toward applying advanced metaheuristics to complex problems in bioinformatics and graph theory. His work increasingly focuses on topological approaches to variable neighborhood search, cancer phylogeny inference, and complex network analysis in biological systems. This represents a maturation of his research from foundational work in evolutionary algorithms to sophisticated applications in computational biology and network science. Best Practice in the area of the 'Introduction of the IT in Service Provision Process' awarded by Union of Municipalities of Montenegro (December 2010) Best Paper Prize award for 'Two Hybrid Genetic Algorithms for Solving the Super-Peer Selection Problem' presented at Online World Conference on Soft Computing in Industrial Applications, WSC 2008 Dr. Filipović has supervised numerous Master's students at both University of Belgrade and University of Banja Luka, with over 25 successful thesis completions. His professional activities extend beyond academia to include leadership in significant IT projects such as the 'eMunicipality' system for city administration, the 'Polyclinic' information system, and digitalization projects for cultural heritage institutions like the Bar County Museum. He has also been involved in educational initiatives including developing new study programs and translating computer science textbooks. He is actively involved with several professional organizations including IEEE Systems, Men and Cybernetics Society - Technical Committee for Soft Computing, IEEE Computational Intelligence Society, IEEE Big Data Community, Mathematical Society of Serbia, and The Heritage Forum of Serbia. His work with the Modelling and optimization group at University of Belgrade represents a significant research hub for computational optimization methods.

Asia van de Mortel-FronczakView profile

Assistant Professor

• Model-Based Engineering
• Supervisory Control Systems
• Discrete-Event Systems
• +4 more

Asia van de Mortel-Fronczak is an Assistant Professor at the Mechanical Engineering Department of Eindhoven University of Technology (TU/e) , where she has been since 1997. Her work focuses on model-based engineering and synthesis of supervisory control systems , with applications in cyber-physical systems like wafer scanners, high-volume printers, vehicles with ADAS, and dynamic traffic infrastructure (e.g., water locks, moveable bridges, tunnels). Academic Background : MSc (1982) and PhD (1993) in Computer Science from AGH University of Science and Technology and TU/e, respectively. Research : Formal models for supervisory control, synthesis-based engineering (SBE), and verification techniques using tools like mCRL2. Her work bridges discrete-event control theory with real-time industrial implementations. Recent Trends : Recent articles highlight her focus on distributed supervisory controllers , communication delay robustness , and dynamic traffic management using formal methods like ACP and ILP. Teaching : Offers courses on supervisory control, model-based systems engineering, and cyber-physical systems. Collaborations : Works with Rijkswaterstaat and ASML, applying her research to real-world systems like ship locks and road tunnels.

Cor HurkensView profile

Assistant Professor

• Operations Research
• Combinatorial Optimization
• Algorithms
• +6 more

Cor Hurkens is an Assistant Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e). His expertise spans operations research, combinatorial optimization, algorithm design, and applied mathematical modeling. Research Focus : Worst-case analysis of combinatorial algorithms, complexity of combinatorial problems, polyhedral theory, and local search approximation methods. Educational Contributions : Supervision of industrial projects and master projects, with a strong emphasis on mathematical modeling in the curriculum. Publications Analysis : His work addresses optimization problems in diverse domains, including Traveling Salesman Problem heuristics , path packing algorithms , optical router revenue maximization , and classification tree learning via column generation . Grants : Supported by the NWO Gravitation project NETWORKS (Grant Number 024.002.003).

L.A.M. SchoenmakersView profile

Associate Professor

• Cryptography
• Secure Multiparty Computation
• Secret Sharing
• +8 more

L.A.M. (Berry) Schoenmakers is an Associate Professor at the Coding Theory and Cryptology department of Eindhoven University of Technology. His research spans cryptography, secure computation, and algorithm design, with a focus on threshold systems and numerical methods in cryptographic contexts. Active in Secure Multiparty Computation , Secret Sharing , and Elliptic Curve Cryptography Published extensively in Cryptography , Fixed-Point Arithmetic , and Algorithm Design Recent work includes secure implementations of Newton-Raphson iteration and Extended GCD algorithms . He teaches courses in Cryptographic Protocols , Linear Algebra , and Programming , with active supervision of research outputs.

Koen KokView profile

Professor

• Smart Grids
• Artificial Intelligence in Energy Systems
• Distributed Energy Systems
• +3 more

Koen Kok is a Full Professor in the Electrical Engineering Department at Eindhoven University of Technology , specializing in Intelligent Energy Systems . He pioneers research in applying distributed software technologies and AI to modernize electricity systems, with a focus on edge computing, market trade, and grid stability. Dutch Research Council (NWO) Perspective Grant (2021) for MegaMind Co-PI in EU projects: ValueFlex, EcoGrid.EU, SmartHouse/SmartGrid Co-author of 2025 publications on MARL algorithms, congestion management, and TSO-DSO coordination Recipient of Blue Tulip and Sustainia100 awards His research bridges technical and ethical aspects of AI in energy systems, emphasizing open-source deployment and commercialization. Current projects include hybrid local electricity markets, grid-edge data integration (MEGAMIND program), and congestion management frameworks combining tariffs and contracts. Recent work demonstrates: Attention-MADDPG algorithm outperforming peers in LEM simulations Seasonal peak tariffs' effectiveness in mitigating load synchronization Integrated TSO-DSO coordination for DER flexibility utilization He leads the MegaMind research program and contributes to EU policy alignment through technical-economic analysis.

George PapafotiouView profile

Professor

• Power Electronics
• Model Predictive Control (MPC)
• Renewable Energy Systems
• +3 more

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.

C.P.M. van HoeselView profile

Professor

• Operations Research
• Optimization Algorithms
• Logistics and Supply Chain Management
• +3 more

Prof C.P.M. van Hoesel is a Professor of Operations Research at Maastricht University's School of Business and Economics, affiliated with the QE Operations research group within the Quantitative Economics department. His research focuses on optimization algorithms, logistics systems, transportation networks, and mathematical programming applications in operations research. Recent work addresses order picking optimization in warehouses, service network design under uncertainty, and routing problems using TSP extensions. Publications span topics from warehouse inventory routing to synchromodal transport pricing strategies, reflecting expertise in both theoretical and applied operations research. Collaborations include work with researchers like Christof Defryn and Faezeh Rajabighamchi on algorithmic solutions for complex logistical challenges. His methodologies combine exact mathematical models with heuristic approaches to solve real-world optimization problems. Key contributions include integer programming applications for disaster risk reduction (e.g., dike height optimization) and robust graph coloring algorithms. Research consistently bridges academic rigor with practical industry applications in logistics, transportation, and supply chain management.

Hans BodlaenderView profile

Professor

• Algorithms
• Complexity Theory
• Graph Theory
• +4 more

Prof. Dr. Hans Bodlaender is a Full Professor of Algorithms and Complexity at Utrecht University's Faculty of Science, Department of Information and Computing Sciences. He holds a Ph.D. in Mathematics from Utrecht University (1985) and has held academic positions since 1983, including roles at Eindhoven University of Technology. His research focuses on algorithms, computational complexity, graph theory, and parameterized complexity, with a particular emphasis on treewidth and network algorithms. He has been recognized with the EATCS-IPEC Nerode Prize (2014) and has contributed to over 500 publications. His work includes developing algorithms for graph decomposition, scheduling, and NP-hard problem analysis. He has organized international workshops and served on editorial boards, including the Journal of Discrete Algorithms. Education: B.Sc. Mathematics, Utrecht University (1981) M.Sc. Mathematics, Utrecht University (1983) Ph.D. in Distributed Computing (1985), supervised by Jan van Leeuwen Research Interests: Algorithms, complexity theory, parameterized complexity, treewidth, graph algorithms, network optimization, and computational problem-solving. His work bridges theoretical foundations with practical algorithm design, emphasizing efficient algorithms for NP-hard problems. Recent Article Trends: Focus on parameterized complexity, treewidth applications, scheduling algorithms, and algorithmic lower bounds. Recent work explores fixed-parameter tractability, graph decompositions, and hardness results for problems on structured graphs. Awards: EATCS-IPEC Nerode Prize (2014) for contributions to parameterized complexity. Grants/Advising: Extensive involvement in grant-funded research projects and academic leadership roles. Supervised numerous PhD and Master's students (details not fully listed here). Labs/Teams: Active in the Algorithms and Complexity research group at Utrecht University, collaborating on theoretical computer science and algorithmic challenges.

• Optimization Models
• Systems and Control
• Cyber-Socio-Technical Systems
• +3 more

Mauro R.U. Salazar Villalon is an Assistant Professor at Eindhoven University of Technology (TU/e) in the Department of Mechanical Engineering and co-affiliated with the Eindhoven AI Systems Institute (EAISI). He obtained his B.Sc. and M.Sc. from ETH Zurich, followed by a Ph.D. from ETH Zurich in collaboration with Ferrari Formula 1. After postdoctoral work at Stanford's Autonomous Systems Lab, he joined TU/e in 2020. Educational Background: B.Sc. & M.Sc. in Mechanical Engineering, ETH Zurich Ph.D. in Mechanical Engineering, ETH Zurich (with Ferrari F1) His research focuses on optimization models for cyber-socio-technical systems, addressing challenges in mobility, pandemics, and material design. He develops methods for sustainable transportation systems, including incentive schemes for user behavior alignment. Recent trends in his publications span hydrogen-based hybrid aero engines, ride-pooling network flows, battery-electric truck infrastructure, and electric vehicle powertrain optimization. His work integrates advanced mathematical modeling with real-world applications. Scientific Awards: ETH Medal (Master & PhD theses) Best Student Paper Awards (2018, 2022) Best Teacher Award (2021) Nominated for TU/e Young Researcher Award (2022) IEEE VPPC 2024 Best Paper Award He contributes to projects like Model Predictive Pandemic Control and National Growth Fund initiatives, while teaching courses on powertrain design, engineering optimization, and optimal control. Collaborations extend to Stanford University and the Ferrari Formula 1 team.

Caroline JagtenbergView profile

Assistant Professor

• Operations Research
• Emergency Medical Services Optimization
• Healthcare Logistics
• +4 more

Dr. Caroline Jagtenberg is an Assistant Professor in the Department of Operations Analytics at the School of Business and Economics, Vrije Universiteit Amsterdam. Her expertise lies in operations research applied to emergency service optimization, healthcare logistics, and fair resource allocation. She holds a PhD in applied mathematics from CWI (2017) and conducted postdoctoral research at the University of Auckland (2018). Education: PhD in Applied Mathematics, Centrum Wiskunde & Informatica (CWI), 2017 Postdoctoral Fellowship, University of Auckland, New Zealand, 2018–2020 Research Interests: Dr. Jagtenberg focuses on bridging theoretical optimization and practical applications in emergency services. Her work includes ambulance and air ambulance base location optimization, community first responder systems, police response time reduction, and fairness in healthcare resource allocation. She has contributed to projects such as the VeRoLog Solver Challenge (Third Prize, 2019) and the NWO Rubicon-funded postdoctoral research. Awards & Grants: Jo van Nunen Award (2017) for best Dutch logistics dissertation NWO Rubicon Grant (2018), supporting her postdoctoral research TKI Dinalog Grant (2023) for the SPRINTER project on emergency response optimization Advising & Projects: She leads the SPRINTER project and contributes to the TKI Dinalog initiative. Ancillary activities include editorial roles at Stator , LNMB board membership, and consultancy with organizations like Deltares and Berenschot. Labs & Teams: Her research leverages datasets such as ambulance travel times (RIVM) and Norwegian municipality data, collaborating on projects like optimizing mobile stroke units and electric ambulance deployment strategies.

Matthias WalterView profile

Assistant Professor

• Operations Research
• Optimization
• Mathematical Programming
• +5 more

Matthias Walter is an Assistant Professor in the Department of Mathematics of Operations Research. His research focuses on optimization, mathematical programming, and algorithm design, with applications in transportation, combinatorial optimization, and logistics. He contributes to the SCIP Optimization Suite and has developed the Combinatorial Matrix Recognition Library. His work spans topics such as linear programming relaxations, pseudo-Boolean solving, and multilinear optimization. Key research interests include operations research, integer programming, and algorithmic solutions for complex optimization problems. He has collaborated on projects like optimizing parcel transportation and analyzing congestion games. His recent publications address challenges in flow shop scheduling, graph realization, and pseudo-Boolean functions. Walter actively participates in academic activities, organizing events like the Mathematical Olympiad in Saxony-Anhalt and presenting invited talks on topics such as McCormick relaxations. His contributions to computational tools and theoretical advancements highlight his role in advancing optimization methodologies.

Ruben Pieter HoeksmaView profile

Assistant Professor

• Transportation
• Agent-Based Modeling
• Traffic Optimization
• +3 more

Ruben Pieter Hoeksma is an Assistant Professor affiliated with the Digital Society Institute and the Mathematics of Operations Research department. His research focuses on algorithmic game theory, transportation optimization, agent-based modeling, and mathematical programming. He actively contributes to advancing methodologies in scheduling, stochastic algorithms, and combinatorial optimization. His work bridges theoretical computer science and practical applications, such as logistics optimization for parcel delivery systems (e.g., PostNL) and robust scheduling under uncertainty. Collaborations span international institutions, reflecting his global academic network. Hoeksma has published extensively in top journals and conferences, with recent contributions addressing congestion games, stochastic minimum spanning trees, and succinct predictions in paging algorithms. His research has been cited 225 times, achieving an h-index of 7.

• Sustainable Process Technology
• Process Optimization
• Carbon Capture and Utilization
• +3 more

Edwin Zondervan is a Full Professor in Sustainable Process Technology, specializing in process optimization, renewable energy systems, and carbon capture technologies. His work contributes to UN Sustainable Development Goals related to affordable and clean energy, climate action, and industry innovation. Research focuses on biofuel production, green hydrogen systems, and sustainable process design through superstructure optimization frameworks. He actively engages in interdisciplinary studies, integrating data-driven methods and digital twin technologies to address energy transition challenges. Recent research highlights include advancing hydrogen-to-power systems, optimizing biodiesel production with heat integration, and stochastic modeling for biorefinery design. His contributions span academic publications, conference presentations (e.g., 2022 talk on PSE in a changing world), and collaborative projects. Zondervan emphasizes agile education strategies to prepare graduates for evolving industry needs, advocating for process systems engineering as a cornerstone of sustainable development. Key themes in his work include decarbonization pathways, energy storage solutions, and circular economy applications. While no awards are explicitly listed, his high citation count (2,895) and h-index (28) reflect significant academic impact. Ongoing efforts focus on integrating renewable energy systems with industrial processes to achieve net-zero goals.

Konstantinos GkiotsalitisView profile

Assistant Professor

• Transport Modeling
• Traffic Operations
• Public Transport
• +3 more

Konstantinos Gkiotsalitis is an Assistant Professor in Transport Engineering and Management. His research focuses on Transport Modeling, Traffic Operations, Public Transport, and Mobility as a Service (MaaS). Previously, he held roles as Research Scientist (2015–2018) and Research Associate (2012–2015) at NEC Laboratories Europe. His work aligns with UN Sustainable Development Goals, particularly addressing urban mobility challenges. He has contributed datasets to repositories like 4TU.Centre for Research Data, including GTFS-RT data and models for public transport adjustments during crises. Key research areas include optimizing railway maintenance schedules, bus reassignment during disruptions, and shared mobility solutions. His publications emphasize operations research and algorithmic approaches to transportation problems. He has supervised two academic works but no student names are explicitly listed.