Find Academic Supervisors

Layla van der Heide-MartinView profile

Assistant Professor

• Transportation Logistics
• Shared Mobility Systems
• Fleet Design Optimization
• +3 more

Dr. Layla van der Heide-Martin is an Assistant Professor at Eindhoven University of Technology (TU/e), affiliated with the School of Industrial Engineering and Innovation Sciences and the Department of Operations Planning Accounting & Control. She also holds the EAISI Mobility Assistant Professor position. Her research addresses operational challenges in transportation and logistics, specializing in shared mobility systems (carsharing, bikesharing, ride-hailing) and strategic fleet design using advanced optimization methods. Education PhD (Dr. rer. pol.) from Technical University of Munich (2020) MSc in Information Systems from Technical University of Munich (2017) BSc from Cooperative State University Baden-Württemberg (2015) Research Focus Layla investigates transportation logistics through multidisciplinary approaches, including mixed integer programming, Markov decision processes, and game theory. Her work balances strategic planning (e.g., fleet sizing) with operational realities, emphasizing collaborations with methodological experts to solve complex mobility challenges. Recent projects target sustainable freight transport and shared system optimization. Research Output Trends Her 15+ publications (2017-present) focus on optimization algorithms for vehicle routing, shared mobility economics, and sustainable urban transport. Articles in Transportation Science and European Journal of Operational Research demonstrate consistent themes: algorithmic efficiency, policy impact analysis, and integrated transport systems. Awards Dissertation Prize (2021) Best Teacher Propaedeutic, Industria Education Awards (2024) Advising & Projects She supervises 6 PhD students and collaborates with postdoctoral researchers. Current grants include: SYNERCIZE: Zero-emission construction transport networks (2025-2027) Integrated Energy/Logistics Planning for Electric Trucking (2024-2028) Innovative Waterway Transportation 2.0 (2023-2026)

Berry SchoenmakersView profile

Associate Professor

• Cryptography
• Secure Computation
• Algorithms
• +3 more

Berry Schoenmakers is an Associate Professor at the Department of Mathematics and Computer Science, Eindhoven University of Technology (TU/e). He specializes in Cryptography and Secure Computation, with a focus on cryptographic protocols, secure multiparty computation, and algorithm design. His research integrates theoretical foundations with practical implementations, particularly in secure arithmetic operations and numerical methods. He teaches courses including Set theory and algebra , Programming and modelling , Basic linear algebra , and Cryptographic Protocols . His recent work emphasizes advancements in threshold cryptography, fixed-point arithmetic for secure computation, and efficient GCD algorithms. Collaborations include co-authorship with researchers like Stan Korzilius and Toon Segers on topics ranging from secure group protocols to trigonometric function implementations in cryptographic contexts. No ancillary activities or scientific awards are listed in the provided information.

• Algorithms
• Planning
• Constraints
• +7 more

Mathijs de Weerdt is a Full Professor at Delft University of Technology, leading the Algorithmics Group within the Faculty of Electrical Engineering, Mathematics and Computer Science. His research focuses on developing advanced algorithms for planning and scheduling under uncertainty, with applications in energy systems, railway logistics, satellite operations, and agricultural supply chains. He bridges fundamental AI research with practical implementations through collaborations with Dutch National Railways (NS), Shell Recharge, and industry partners. Education: PhD in Multi-Agent Plan Merging (2003), MSc in Computer Science (Utrecht University, cum laude) Research Interests: Robustness in AI, Scalability of Optimization Algorithms, and Multi-Party Coordination His work integrates Stochastic Programming , Reinforcement Learning , and Constraint Programming to address challenges in energy transition and transportation. Recent 15 most recent publications emphasize surrogate modeling for EV charging optimization, multi-agent pathfinding in railways, and dynamic programming for decision trees. Scientific Awards: Recipient of the Erasmus Energy Forum Science Award (2016), Best Teacher Award in Delft Computer Science (2015), and honorable mentions for dissertation and paper awards. As a promotor , he guides over 20 PhD candidates in projects spanning smart grid algorithms, train unit shunting, and strawberry supply chain optimization. He leads large-scale initiatives like the NWO ESI-FAR project and co-chairs the Dutch AI Coalition's Energy & Sustainability working group.

• Algorithms
• Graph Theory
• Network Analysis
• +5 more

Dr. Erik Jan van Leeuwen is an Assistant Professor in the Department of Algorithms and Complexity within the Faculty of Science at Utrecht University. His research focuses on theoretical computer science, particularly in algorithms, graph theory, and computational complexity. He teaches courses including Algorithms, Network Science, and ICS tutorials. His primary research interests include algorithms, graph theory, network analysis, computational complexity, data structures, and computational geometry. Van Leeuwen's work often centers on forbidden subgraph problems, parameterized complexity, and graph algorithms, with significant contributions to understanding the complexity of problems on specific graph classes. His recent publications (2023-2025) demonstrate a strong focus on complexity frameworks for forbidden subgraphs, with multiple papers exploring different aspects of this framework. He has made significant contributions to understanding the complexity of problems like vertex covers, disjoint paths, and diameter problems on H-free graphs. His research also extends to parameterized complexity, streaming algorithms, and network design problems, showing a diverse yet cohesive research program in theoretical computer science. Dr. van Leeuwen is actively involved in the Foundations of Complex Systems and the Utrecht Platform for Applied Data Science, connecting his theoretical work with broader applications. His research has been consistently published in top theoretical computer science venues including Algorithmica, SIAM Journal on Discrete Mathematics, and conference proceedings from major algorithms conferences.

Judith KeijsperView profile

Lecturer

• Graph Algorithms
• Computational Biology
• Combinatorial Optimization
• +4 more

Judith Keijsper is a Lecturer at the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e) , where she has been affiliated since 2000. She works within the Combinatorial Optimization group, focusing on graph algorithms and their applications in computational biology. She teaches courses such as Graph Theory, Linear Algebra, and Discrete Dynamical Systems. Her research spans phylogenetic network reconstruction, haplotyping complexity, and discrete optimization. Key themes include Unrooted binary phylogenetic level-1/level-2 networks Polynomial time algorithms for NP-hard problems Applications of graph theory to biological data Linear equation systems over GF(2) Her publications demonstrate expertise in algorithm design for genetic analysis and evolutionary modeling. No scientific awards are explicitly mentioned in the provided texts.

P. PalenskyView profile

Professor

• Power Systems
• Simulation
• Grids
• +9 more

Prof. P. Palensky is a full Professor at the Electrical Sustainable Energy Department within the College of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. His work focuses on power systems, grids, and energy systems with an emphasis on simulation, control, and optimization. Research Themes: Cyber-physical power systems, multi-energy systems, voltage control, distributed energy resources, smart grids, and hybrid deep learning frameworks. Recent Work: 2025 studies include energy storage dispatch optimization, anomaly detection in grids, and phase identification models. Awards: Recipient of the Hidde Nijland Prize (2022) for outstanding contributions to energy technology. Collaborations: Active in the TwinEU consortium project and partnerships with Alliander and PowerWeb Institute.

Dennis HuismanView profile

Professor

• Public Transport Optimization
• Railway Logistics
• Crew Scheduling
• +1 more

Dennis Huisman is Professor of Public Transport Optimization at Erasmus School of Economics and Expertise Manager at Netherlands Railways. His research develops operations research models for railway logistics, including real-time crew rescheduling algorithms implemented nationally. He co-founded the Erasmus Center for Optimization in Public Transport. Research Interests: Railway timetable robustness, integrated vehicle-crew scheduling, disruption recovery in transit networks. Awards: INFORMS Franz Edelman Award (2008) ERIM Impact Award

Olga KuryatnikovaView profile

Assistant Professor

• Non-linear optimization
• Convex programming
• Network optimization
• +3 more

Dr. Olga Kuryatnikova is an Assistant Professor at the Econometric Institute within Erasmus School of Economics, Erasmus University Rotterdam. She specializes in developing solution approaches for non-linear optimization problems using convex programming, with applications in energy, transport, and network systems. Previously, she worked as a financial analyst in industry. Her research focuses on optimization over networks, energy systems, and machine learning applications. She holds a PhD in Operations Research from Tilburg University and an MSc in Econometrics and Operations Research (cum laude). Kuryatnikova teaches courses including Linear Programming, Optimization under Uncertainty, and Convex Analysis for Optimization. She coordinates Erasmus University's Sectorplan SSH-Breed initiative on societal effects of digitalization.

• Retail Operations
• Revenue Management
• Logistics Optimization
• +2 more

Dr. Nevin Mutlu is an Assistant Professor at Eindhoven University of Technology's School of Industrial Engineering, affiliated with the Operations Planning Accounting & Control group. She holds appointments with the Data Science Center Eindhoven and Freight Transport & Logistics Research Group. Her educational background includes a PhD and MSc in Industrial and Systems Engineering from Virginia Tech, and dual BA/BSc degrees in Economics and Industrial Engineering from University at Buffalo. Research focus areas: Pricing and revenue management in omnichannel retail Logistics optimization with behavioral considerations Demand steering mechanisms Market equilibrium in experiential retail Publication analysis shows progression from fundamental optimization methods to behavioral operations, with recent work incorporating consumer psychology into operational models. Awards include the prestigious EU Horizon 2020 Marie Curie Individual Fellowship. She currently leads the SYNERCIZE project on sustainable transport networks and serves on industry committees including the Efficient Consumer Response Community. Teaching includes Revenue Management and Pricing Analytics, Supply Chain Management, and Project Process Management courses.

Paolo GorgiView profile

Associate Professor

• Score-driven time series models
• Stochastic processes
• Forecasting economic variables
• +3 more

Dr. Paolo Gorgi is an Associate Professor at the Department of Econometrics and Data Science in the School of Business and Economics at Vrije Universiteit Amsterdam. He holds a PhD in Statistics and Econometrics from the Joint Degree Program of the University of Padova and Vrije Universiteit Amsterdam (2017). His research focuses on score-driven time series models, stochastic processes, forecasting economic variables, and statistical inference in non-linear dynamic models. He is also a Partner at ACMetric B.V. since 2021. His work contributes to UN Sustainable Development Goals related to economic growth and sustainable cities. Key research interests include developing novel methodologies for time series analysis, particularly in handling non-linear dynamics and high-dimensional data. He has authored over 36 publications, including influential works on score-driven models, copula-based count models, and robust statistical estimation techniques. Teaching responsibilities include courses on Data Science Methods and Financial Econometrics . His research network spans collaborations with institutions globally, focusing on econometric applications in finance, macroeconomics, and sports analytics. He has supervised two PhD theses and actively contributes to the academic community through editorial roles and conference participation.

• Healthcare Operations Management
• Operations Research
• Health Informatics
• +3 more

Gréanne Leeftink is an Associate Professor at Utrecht University, holding roles in the Digital Society Institute, Industrial Engineering & Business Information Systems, and TechMed Centre. Her research focuses on optimizing healthcare operations through advanced analytics, process mining, and operations research, addressing challenges such as nurse allocation, bed census prediction, and inter-organizational resource pooling. She earned her PhD from Utrecht University with a thesis on healthcare process optimization. Her expertise spans healthcare logistics, scheduling strategies, and simulation-optimization methods. Key contributions include models for hospital capacity planning, cost analysis of Connected Care interventions, and reducing failures in medical practices. She has organized conferences like the CHOIR PhD Summer School on Healthcare Operations Research. Scientific Awards: CTIT Best poster award (2015) NWO MaGW Research Talent Grant (2014) Prins Bernhard Cultuurfonds grant (2016) Gréanne collaborates across disciplines to improve healthcare systems, emphasizing data-driven decision-making and sustainable resource management. She has supervised one PhD student and contributed to grants focusing on integrated healthcare processes and rapid diagnostics.

Iris VisView profile

Professor

• Logistics
• Supply Chain Management
• Container Terminal Optimization
• +5 more

Iris Vis is a Professor of Industrial Engineering at the Faculty of Economics and Business, University of Groningen. Her expertise lies in the design and optimization of complex logistics systems, with particular focus on container terminals, vehicle routing, inventory management, and sustainable supply chains. She has established herself as a leading researcher in operations management and operations research, with strong connections to both academic and industry partners. Vis earned her Master's degree in Mathematics from Leiden University and completed her PhD at Erasmus University Rotterdam. Prior to joining the University of Groningen, she served as an Associate Professor at VU University Amsterdam. She has held visiting researcher positions at CIRRELT (Canada), Virginia Tech (USA), and Georgia Institute of Technology (USA), establishing an international research network. Her research interests span multiple domains within logistics and operations management, with recent emphasis on sustainable transport solutions, LNG as an alternative fuel, and the application of mathematical modeling to optimize complex systems. Vis has pioneered the application of Lean principles to educational logistics, working with secondary schools to optimize personalized learning processes. Her work bridges theoretical operations research with practical applications in maritime transport, energy infrastructure, and supply chain management. Analysis of her recent publications shows a clear trend toward sustainability-focused logistics research, with increasing attention to renewable energy integration, alternative fuels (particularly LNG), and environmentally conscious supply chain design. Her work combines rigorous mathematical modeling with practical implementation considerations, making significant contributions to both academic literature and industry practice. Captain of Science of the Top Sector Logistics (2023) Presentation of research results to Queen Máxima Multiple NWO grants for sustainable logistics research Vis has extensive experience collaborating with industry partners, having served as Dean of Industry Relations at the University of Groningen. She actively seeks engagement with businesses and non-profit organizations through direct visits and collaborative projects that bridge fundamental research questions with practical business challenges. Her research has led to numerous industry implementations, particularly in the areas of sustainable transport and logistics optimization. She frequently presents research findings at in-house company trainings and professional conferences. Her work with Groningen Seaports and the logistics industry has established her as a key figure in developing sustainable transport solutions. She leads research teams focused on optimizing container terminal operations, vehicle routing, and inventory management systems, with particular attention to environmental sustainability. Her collaboration with the Top Sector Logistics has positioned her at the forefront of Dutch logistics research and innovation.

Marleen BalvertView profile

Assistant Professor

• Optimization
• Machine Learning
• Genomics
• +3 more

Marleen Balvert is an Assistant Professor at Tilburg University's Tilburg School of Economics and Management (TiSEM), Department of Econometrics and Operations Research. Her research focuses on applying optimization and machine learning to address challenges in the medical and humanitarian sectors. She leads projects such as the Zero Hunger Lab, developing tools to improve food security operations, and collaborates with institutions like the World Food Program and Erasmus Medical Center. Her work includes creating the ARAN dataset for child health monitoring and optimizing radiotherapy workflows in healthcare. Key research interests include genomics data analysis for disease identification, resilient food systems, and interpretable machine learning methods. She teaches courses on operations research and machine learning at TiSEM. Balvert has been awarded the NWO Veni Grant and actively contributes to interdisciplinary projects bridging academia and real-world applications. Her recent publications emphasize data-driven solutions in healthcare and humanitarian logistics, with collaborations spanning bioinformatics, medical research, and global hunger initiatives.

Wilco van den HeuvelView profile

Associate Professor

• Operations Research
• Production Planning
• Supply Chain Optimization
• +7 more

Wilco van den Heuvel is an Associate Professor at the Econometric Institute within the Erasmus School of Economics, Erasmus University Rotterdam. His research lies at the intersection of operations research and production planning, with a focus on algorithmic solutions for lot-sizing and supply chain optimization problems. Research Interests: His primary research interests include deterministic production planning, extensions of the economic lot-sizing model, and the development of efficient algorithms. He actively investigates integrated problems involving production, maintenance, and logistics, with increasing applications in reinforcement learning and customer-centric return systems. His work spans theoretical complexity analysis and practical implementations in real-world supply chains. Recent Research Trends: Analysis of his recent publications reveals a strong focus on integrated optimization models, particularly combining lot sizing with maintenance and market selection. There is a growing interest in data-driven logistics, as seen in his work on hierarchical clustering and customer-to-customer returns using reinforcement learning techniques. His research consistently targets computational efficiency and scalability. Scientific Service: Editorial Board Member, IISE Transactions (since June 2019) Editorial Board Member, Omega (United Kingdom) (since May 2014) Advising and Research Output: He has supervised multiple research projects and co-authored a doctoral thesis on exact methods for hierarchical clustering. His research output includes over 80 contributions, with recent work published in top-tier journals such as Operations Research , European Journal of Operational Research , and Omega . He is actively involved in both theoretical and applied operations research, contributing to software implementations and real-world logistics solutions. Collaborative Networks: His research collaborations span multiple institutions, with a strong presence in European operations research networks. His work frequently involves interdisciplinary teams focusing on supply chain innovation and computational optimization.

• Robotics
• Operations Management
• Microbiology
• +3 more

Zhongqiang Ma holds a Visiting fellow position in the Department of Technology and Operations Management at Rotterdam School of Management, demonstrating active engagement in two distinct research domains: industrial robotics and clinical microbiology. His interdisciplinary profile bridges engineering and life sciences through methodical investigations into warehouse automation systems and gut-health biomarkers. Research Interests: Ma's scholarly focus spans Robotics , Operations Management , Microbiology , and Gut Microbiota analysis. His robotics work develops algorithmic solutions for travel-distance minimization in automated fulfillment centers using mixed integer programming, while his microbiological research establishes quantitative relationships between intestinal bacterial populations (particularly Streptococcus species) and metabolic health indicators like body mass index. This dual expertise enables cross-pollination of computational optimization techniques and biomedical data analysis. Publication Trends: Ma's 2022-2025 output reveals a strategic interdisciplinary trajectory—his 2025 International Journal of Production Research article advances robotic logistics through Pareto frontier modeling of storage systems, whereas his 2022 Beneficial Microbes study contributes epidemiological evidence linking gut flora composition to obesity metrics in Chinese adult populations. Both publications demonstrate rigorous quantitative methodologies applied to real-world systems, with Scopus citations confirming impact in both engineering and medical domains. Scientific Recognition: No formal awards, fellowships, or honorific distinctions are documented in the provided materials Academic Mentoring: No student supervision records or educational leadership roles are specified Grant funding sources remain undisclosed in available documentation Research Infrastructure: Collaborative patterns suggest affiliation with robotics testbeds for warehouse automation studies (evidenced by co-authorship with de Koster and Roy) and clinical microbiology facilities for gut flora analysis (indicated by partnerships with Peppelenbosch and Chinese medical researchers), though dedicated laboratory spaces aren't explicitly described.