Find Academic Supervisors

Sander StuijkView profile

Associate Professor

• Embedded Systems
• Signal Processing
• Multi-Core Architectures
• +3 more

Sander Stuijk is an associate professor at the Department of Electrical Engineering of Eindhoven University of Technology, chairing the Electronic Systems (ES) group. His research focuses on design methodologies for embedded signal processing applications in high-tech systems like industrial manufacturing, automotive, and healthcare. He develops high-level compilation strategies for heterogeneous multi-core platforms, with interests in efficient code generation and resource allocation. Prof. Stuijk holds leadership roles including chairing the ES group, serving on the board of 4TU.NIRICT (a Dutch ICT research consortium), and coordinating the Embedded Systems master program. He contributes to national ICT initiatives through ICT Next Generation, a network for mid-career academics. He also chaired the Department Council (2016-2018) and participates in TPC activities. His research spans streaming applications, real-time systems, and multi-processor architectures. Notable projects include the PROMES initiative (programming embedded multi-media systems) and the MNEMEE project (automated MPSoC design). His work emphasizes predictable and energy-efficient computing, with applications in healthcare monitoring (e.g., remote PPG, thermal imaging) and reconfigurable systems. Prof. Stuijk has advised numerous PhD/Master students and led projects like FORSEE, VSM, and SenSafety. His publications include over 70 journal/conference papers, covering topics like neuromorphic computing, GPU optimization, and medical signal processing. He actively engages in academic service, including organizing SCOPES workshops and serving on editorial boards.

Alessandro GabbanaView profile

Researcher

• Computational Fluid Dynamics
• Lattice-Boltzmann Method
• Turbulence Modeling
• +3 more

Alessandro Gabbana is a University Researcher at Eindhoven University of Technology, affiliated with the Applied Physics and Science Education school and the Computational Multiscale Transport Phenomena group. His research focuses on computational physics, particularly lattice-Boltzmann methods and fluid dynamics. He co-leads the HTCrowd project (2020–2026), developing high-tech platforms for human crowd flow monitoring and modeling. Research interests span: Advanced computational fluid dynamics (CFD) Turbulence subgrid modeling using data-driven approaches Pedestrian dynamics and probabilistic flow analysis Neural network integration with kinetic schemes His publications demonstrate strong emphasis on improving lattice-Boltzmann boundary conditions, turbulence closures, and large-scale pedestrian dynamics simulations.

Dinesh KallurView profile

Assistant Professor

• Distributed Optimization
• Numerical Optimal Control
• Real-Time Optimization
• +4 more

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.

Remco DijkmanView profile

Professor

• Business Process Management
• Data-driven Optimization
• Quantitative Business Process Analysis
• +4 more

Remco Dijkman is a Full Professor in Information Systems and chair of the Information Systems group at Eindhoven University of Technology (TU/e) within the Industrial Engineering and Innovation Sciences school. He leads research in Business Process Management with a focus on data-driven optimization of business processes. His work bridges theoretical advancements with practical applications in transportation and high-tech supply chains. Dr. Dijkman received his PhD and Master's degrees in computer science from the University of Twente. His academic journey includes visiting positions at New York University, Hasso Plattner Institute, IBM Zurich Research Lab, Humboldt-University Berlin, and Queensland University of Technology. PhD in Computer Science - University of Twente Master's in Computer Science - University of Twente Professor Dijkman's research focuses on the detection, diagnosis and prediction of optimal execution scenarios, mathematical models for quantitative analysis of business processes, and resource assignment optimization. His work integrates advanced techniques including queueing models, stochastic programming, and deep reinforcement learning to solve complex business process challenges. He has particular expertise in applying these methods to transportation logistics and high-tech supply chain planning, where he investigates how data-driven predictions can improve transport order assignment and supply chain planning. His recent publications demonstrate a strong trend toward integrating artificial intelligence techniques with traditional operations research methods. The research shows increasing sophistication in handling uncertainty in business processes, with a growing emphasis on real-time decision making and optimization. His work spans theoretical advancements in process modeling and practical applications in logistics and supply chain management, reflecting his commitment to bridging academic research with industry needs. Professor Dijkman serves on the editorial board of Information Systems journal and has published over 100 papers in prestigious venues including Information Systems, Computers in Industry, and Transactions on Software Engineering and Methodology. He currently leads or participates in several major research projects including DynaPlex, CERTIF-AI, SLEM, and FENIX. Additionally, he serves as research director for high-tech supply chain at the European Supply Chain Forum, a networking organization with over 50 multinational companies. His adjunct professorship at Queensland University of Technology demonstrates his international academic engagement. Professor Dijkman's research group focuses on developing advanced methods for business process analysis and optimization, with particular emphasis on handling uncertainty and making real-time decisions in complex business environments. The team works closely with industry partners to ensure practical relevance of their research, particularly in transportation and high-tech manufacturing sectors.

Alexander SerebrenikView profile

Professor

• Social Software Engineering
• Empirical Software Engineering
• Socio-Technical Coordination
• +3 more

Alexander Serebrenik is a Full Professor of Social Software Engineering at Eindhoven University of Technology (TU/e), within the Department of Mathematics and Computer Science. He specializes in empirical software engineering, focusing on the socio-technical aspects of software development. His research bridges computer science and organizational psychology, emphasizing observation and experimentation. Serebrenik holds a PhD from KU Leuven and an MSc from the Hebrew University of Jerusalem. He has held academic positions across Europe, including postdoctoral roles in Belgium and France. Notably, he served as a part-time visiting researcher at CWI until 2017. His work includes over 100 publications, including co-authoring the book Evolving Software Systems . He actively contributes to conference organization and editorial boards, receiving multiple best paper and distinguished reviewer awards. Current teaching includes courses on empirical methods and software engineering. His research explores developer interactions with bots, gender diversity in GitHub teams, and strategies for veteran women developers. He advocates for integrating human factors into software tools and workflows. Education Background: PhD in Computer Science (KU Leuven), MSc in Computer Science (Hebrew University), with postdoctoral and visiting roles at Ecole Polytechnique (France), University of Mons, and University of Bari. Research Interests: Social Software Engineering, Human-Computer Interaction in Development, Empirical Methods, Technical Debt, Diversity in Tech, Bot Integration, and Open Source Communities. Key Publications Trends: Recent works focus on GitHub bots' autonomy preferences, veteran women developers' experiences, and dependency security tools like Dependabot. Themes emphasize human factors, collaboration dynamics, and ethical software practices. Scientific Awards: Best Paper Awards, Distinguished Reviewer Awards, IEEE Senior Membership Advising & Grants: Active in mentoring and securing grants for empirical software engineering projects Labs/Teams: Leads the Social Software Engineering group at TU/e, collaborating on projects like PerfBot for performance assessment and LaMa for thematic labeling.

Rob WolfsView profile

Assistant Professor

• 3D Concrete Printing
• Digital Design and Manufacturing
• Robotics in Construction
• +4 more

Rob Wolfs is an Assistant Professor at Eindhoven University of Technology (TU/e) in the unit of Structural Engineering and Design. His research focuses on digital design and manufacturing strategies, particularly 3D concrete printing, aiming to enhance sustainability and productivity in construction. He holds a PhD (cum laude, 2019) and MSc from TU/e and has received notable awards including the 2022 Veni Grant (NWO) and the 2024 RILEM Gustavo Colonnetti Medal. Education: MSc in Structural Engineering and Design, TU/e (2015) PhD in 3D Concrete Printing, TU/e (2019) Research Interests: Robotics in construction, numerical modeling, machine learning, structural optimization, and quality control in 3D printing. His work bridges theoretical advancements and industrial applications, emphasizing environmental impact reduction through innovative fabrication methods. Collaborations: Visiting researcher at IFSTTAR Laboratoire Navier (France), DTU (Denmark), and CY University (France via PHC Van Gogh grant). Editor for Materials & Structures (Springer). Labs/Teams: Leads the 3D Concrete Printing group and contributes to EAISI High Tech Systems at TU/e.

Maarten SchoukensView profile

Associate Professor

• Nonlinear System Identification
• Machine Learning for Control Systems
• Data-Driven Modeling
• +5 more

Maarten Schoukens is an Associate Professor in the Control Systems group at the Department of Electrical Engineering, Eindhoven University of Technology. He holds a PhD from Vrije Universiteit Brussel (2015) and has held postdoctoral positions at both VUB and TU/e. His research focuses on nonlinear system identification, machine learning applications in control, and data-driven modeling of complex systems. He has received prestigious awards including an ERC Starting Grant (2022) and an EU Marie Skłodowska-Curie Fellowship (2018). He leads projects like DAMOCLES (2021–2025) and CELLSYSTEMICS (2022–2026), advancing constitutive law modeling and human measurement systems. Active in editorial roles for IEEE and ECC conferences, he also co-organizes the nonlinearbenchmark.org initiative. Education: MSc and PhD in Electrical Engineering from VUB (2010–2015). Postdoctoral Researcher at TU/e (2017–2018) before becoming Assistant Professor (2018) and later Associate Professor (2023). Research emphasizes nonlinear dynamical systems, with contributions to system identification, neural network architectures for control, and frequency-domain methods. Key projects include developing LPV control strategies and physics-guided learning frameworks. His work bridges classical control theory with modern machine learning, addressing challenges in autonomous systems and high-tech engineering. Awards include FWO PhD Fellowship (2011), Marie Skłodowska-Curie Fellowship (2018), and ERC Starting Grant (2022). Supervised over 15 graduate students and led multidisciplinary teams in EU-funded initiatives. Labs include the Autonomous Motion Control Lab and High Tech Systems Center, fostering collaborations in robotics, aerospace, and biomedical engineering.

Loek G.W.A. CleophasView profile

Assistant Professor

• Model-Driven Software Engineering
• Algorithm Engineering
• Pattern Matching
• +5 more

Loek G.W.A. Cleophas is an Assistant Professor in Engineering of Software-Intensive Systems at Eindhoven University of Technology (TU/e), affiliated with the Mathematics and Computer Science department. He holds an Extraordinary Associate Professorship at Stellenbosch University and has held visiting roles at TU Braunschweig (2016-2017) and Umeå University (2014-2016). His academic career includes industry collaborations with ASML and Canon, and leadership as Managing Director of the Dutch research school for Programming and Algorithmics (IPrA). Education: Both his MSc (with honors) and PhD in Computer Science and Engineering were obtained at TU/e. His research focuses on model-driven software engineering (MDSE) and algorithm engineering, with emphasis on pattern matching using finite automata and parallel processing for large datasets. Recent work includes model repository analytics, digital twin systems, and variability analysis in software product lines. Research Trends: Over 129 publications span topics like SAMOS framework for model analytics, VPDSL domain-specific languages, and taxonomy-based algorithm toolkits. His work bridges theoretical foundations with industrial applications in high-tech systems. Advising: Supervised 27 postgraduate students at Stellenbosch and TU/e. Grants/Projects: Led collaborations with ASML on model-driven virtualization, and organized international workshops like AMMoRe (2018-2020). Labs/Tools: Developed SAMOS framework for model analytics and LaMa web application for thematic labeling. Active in open-source tool development for correctness-by-construction methodologies.

Sebastiaan J.A.M. van den EijndenView profile

Assistant Professor

• Nonlinear Control Systems
• High-Tech Machine Performance
• Control Theory
• +3 more

Sebastiaan J.A.M. van den Eijnden is an Assistant Professor at the Department of Control Systems Technology within the College of Mechanical Engineering at Eindhoven University of Technology. His research focuses on leveraging machine data to develop graphical and algorithmic methods for enhancing the performance of nonlinear control systems in high-tech machinery, emphasizing productivity, precision, and efficiency. He is a key member of the Projection-based Control (PROACTHIS) project (2022–2028), aiming to advance control methodologies for constrained dynamical systems. He teaches courses such as Control Engineering , Hybrid Systems and Control , and Performance of Nonlinear Control Systems . His research interests encompass nonlinear control systems, system stability analysis, motion control, and data-driven approaches. Recent work includes contributions to dissipativity frameworks, nonlinear system characterization, and phase-optimized integrators. He holds a Master’s degree in Mechanical Engineering (thesis: Cascade based tracking control of quadrotors ) and maintains active collaborations in systems engineering and control theory.

Hans VermeulenView profile

Professor

• Precision Engineering
• Control Systems
• Mechatronics
• +3 more

Hans Vermeulen is a Full Professor in Control Systems Technology at Eindhoven University of Technology (TU/e) , specializing in high-performance motion systems and precision engineering. He chairs the Mechatronic Systems Design group and collaborates closely with the High Tech Systems Center (HTSC) and ASML Netherlands BV as Senior Architect of EUV Optics Systems. His roles include academic leadership and industry partnership. Education: PhD in Mechatronics, TU/e MSc in Mechanical Engineering, TU/e MSc in Technological Design/Mechatronics, TU/e Research Interests: Focus on precision mechanics, superconductive motors, thermal control systems, and medical equipment design. His work integrates advanced materials and mechatronics for high-tech applications, with emphasis on reproducibility and accuracy in motion systems. Collaborations span academia and industry, addressing challenges in EUV lithography and mechatronic systems for SMEs/OEMs. Projects & Contributions: Leading the COMEDI project (2024-2029) on cost-effective mechatronic design for high-tech systems. Supervised over 24 academic works, including a master’s thesis on precision diamond turning machines. Labs/Teams: Group Vermeulen (TU/e), High Tech Systems Center (HTSC), and national R&D Workgroup Mechatronics.

Rob J.M. WolfsView profile

Assistant Professor

• 3D Concrete Printing
• Digital Design and Manufacturing
• Robotics in Construction
• +5 more

Rob J.M. Wolfs is an Assistant Professor at Eindhoven University of Technology (TU/e), specializing in Structural Engineering and Design. He holds dual roles as a faculty member in the Built Environment department and as an EAISI High Tech Systems Assistant Professor. His academic background includes a MSc (2015) and a PhD (cum laude, 2019) from TU/e, both focusing on 3D concrete printing. His research emphasizes digital design, robotics-driven construction, and sustainable practices in architecture and engineering. Key interests include 3D concrete printing, quality control, and integration of machine learning for structural optimization. He serves as an Associate Editor for Springer’s Materials & Structures and has received prestigious awards like the 2022 Veni Grant and the 2024 RILEM Medal. Recent articles highlight advancements in quality control frameworks, data-driven manufacturing, and large-scale applications of 3D-printed concrete. His work often bridges theoretical models with practical field implementations, addressing both technical challenges and sustainability goals. Rob frequently collaborates internationally, including visiting research roles at IFSTTAR (France) and DTU (Denmark). He teaches courses on digital design, resource-efficient engineering, and construction technologies. Media engagements include expert commentary on 3D-printed housing and future construction trends.

Ivo AdanView profile

Professor

• Stochastic Operations Research
• Queueing Models
• Manufacturing Systems
• +4 more

Ivo Adan is a Full Professor at Eindhoven University of Technology (TU/e) in the departments of Operations, Planning, Accounting and Control (Industrial Engineering & Innovation Sciences) and Dynamics and Control (Mechanical Engineering). He holds the Manufacturing Networks chair and has held visiting roles at the University of North Carolina and part-time positions at the University of Amsterdam. His research focuses on stochastic operations research, queueing models, and mathematical analysis of manufacturing systems, warehousing, and transportation systems. Adan received both his MSc and PhD in Mathematics from TU/e. He serves on editorial boards for Queueing Systems and Probability in the Engineering and Informational Sciences , and leads Beta, the national network for Operations Management and Logistics. He is a Senior Fellow of Eurandom and has contributed significantly to industry applications through his work on semiconductor manufacturing and logistics optimization. His research explores multi-dimensional Markov processes, variability management in manufacturing, and efficient modeling techniques. Recent work includes optimizing maintenance planning with reinforcement learning, aggregated simulation models for safety stocks, and autonomous mobile robotics in manufacturing systems. Key Awards: Senior Fellow of Eurandom, Research Director of Beta Education: MSc and PhD in Mathematics from TU/e Labs/Teams: EAISI High Tech Systems, Operations Planning & Control group Adan advises on semiconductor simulation studies, poultry processing optimization, and biomanufacturing yield improvements. His interdisciplinary approach bridges theoretical stochastic models with practical industrial challenges.

• Model-Based Design Methods
• Design Automation
• Optimization
• +5 more

Marc Geilen is an Associate Professor at the Electronic Systems group of Eindhoven University of Technology (TU/e) . He leads the Model-Based Design Lab within the CompSOC Lab and High Tech Systems Center .