Michael Tieland is a Senior Lecturer at the Amsterdam University of Applied Sciences, specializing in Nutrition and Exercise. His research focuses on older adults' health, particularly addressing malnutrition, sarcopenia, and the efficacy of combined nutritional and exercise interventions. He leads projects like PROMIO and has contributed to over 80 research outputs, including randomized controlled trials and systematic reviews. Key research interests include protein intake optimization, interprofessional care for malnutrition, and culturally adapted interventions for ethnic minorities. His work spans clinical nutrition, gerontology, and exercise physiology, with a focus on improving physical performance and metabolic health in aging populations. Notable achievements include the 2020 HvA Research of the Year award and contributions to datasets like the 'Transcripts focusgroups older ethnic minorities.' Tieland supervises student theses on topics such as protein supplementation and exercise programs for older adults. His research emphasizes real-world applications, including sustainable dietary strategies and interprofessional collaboration in healthcare.
Akshay Kumar Burusa is a Researcher in the Department of Agricultural Biosystems Engineering at Wageningen University & Research . His work focuses on integrating robotics, computer vision, and deep learning for agricultural automation, particularly in greenhouse environments. Research Interests : Robotics and machine learning for agro-food systems 3D pose estimation and keypoint detection in plants Real-time object tracking in cluttered environments Next-best-view algorithms for plant reconstruction Biomechanical modeling for robotic grasping Recent Publications highlight advancements in agricultural robotics, including multi-view active vision for plant node detection, deep learning-based grasping of deformable objects, and self-supervised 3D reconstruction algorithms. His work emphasizes practical applications in tomato greenhouses and poultry processing automation. Collaborations : Collaborates with experts like Eldert van Henten and Gert Kootstra on projects involving robotic perception and tracking. His research contributes to improving efficiency in agro-food robotics through advanced vision systems and algorithm design.
Rob Basten is an Associate Professor in the Department of Industrial Engineering and Innovation Sciences at Eindhoven University of Technology (TU/e). He has been with TU/e since October 2014, initially as an Assistant Professor before being promoted. His work focuses on operations management and behavioral operations management, with particular expertise in maintenance, spare parts supply, and after-sales services for high-tech equipment. Basten's research is highly applied, often conducted in collaboration with industry partners such as ASML, NXP, Canon Production Printing, Marel Poultry, and the Ministry of Defence. Dr. Basten's educational background includes: Master's in Industrial Engineering and Management (2004) from University of Twente Master's in Computer Science (2005) from University of Twente PhD in Operations Management (2010) from University of Twente Rob Basten's research centers on improving after-sales services for high-tech equipment, with a focus on incorporating new technologies such as 3D printing and IoT. His work spans both analytical and empirical approaches, with increasing emphasis on behavioral operations management as human decision-makers interact with AI-based decision support systems. Basten investigates how to design and control after-sales service supply chains when spare parts can be 3D printed, and how to optimize maintenance policies for complex systems. His interdisciplinary research bridges operations management, maintenance engineering, and human behavior. Analysis of Basten's recent publications reveals a strong focus on the application of new technologies in after-sales services. Key trends include the integration of additive manufacturing in spare parts supply chains, condition-based and predictive maintenance driven by Industry 4.0 technologies, and the behavioral aspects of human-AI collaboration in maintenance decision-making. His work frequently addresses challenges in high-tech manufacturing contexts, particularly semiconductor equipment, with a growing emphasis on Industry 5.0 concepts that integrate human-centered approaches with advanced technologies. Dr. Basten has received recognition for his work, including: Finalist for the 2020 Daniel H. Wagner Prize for Excellence in Operations Research Practice ISIR Best Student Paper Award 2018 Rob Basten actively supervises numerous PhD students and has led several major research projects. He currently supervises nine PhD students including Maryam Azani, Ragnar Eggertsson, Bibi de Jong, Zhao Kang, Niccolò Maccarini, Aran Nasiri, Bas van Oudenhoven, İpek Tanıl, and Alireza Yazdani. He has successfully guided six PhD students to completion. Basten has been project leader and work package leader in significant research initiatives including ProSeLoNext (funded by NWO with industry co-funding), PrimaVera, SINTAS, and OCPROM projects. His research is consistently supported by both public funding agencies and industry partnerships, reflecting the practical relevance of his work. Basten is an active member of the Operations, Planning, Accounting & Control group at TU/e and contributes to the EAISI High Tech Systems initiative. He has organized key academic events including the first two editions of the Maintenance Research Day and the Behavioral Operations Conference 2019. His work connects academic research with industry practice through ongoing collaborations with leading high-tech companies, creating a dynamic research environment focused on solving real-world challenges in maintenance and service logistics.
Yoeri R.J. Poels is a researcher at Eindhoven University of Technology specializing in fusion energy and artificial intelligence applications. His work focuses on enhancing tokamak operations through data-driven modeling and AI techniques, with significant contributions to the Eurofusion Tokamak Exploitation Team and MAST Upgrade collaboration. His research interests bridge fusion energy engineering and artificial intelligence , particularly in developing surrogate models and deep learning algorithms for tokamak control systems. Key areas include power exhaust management, divertor technology, and real-time plasma control solutions for next-generation fusion reactors. His work integrates physics-based modeling with advanced machine learning techniques to address critical challenges in fusion energy development. Analysis of his publication record reveals a strong trajectory in applying AI methods to fusion challenges , with increasing focus on practical implementation in experimental tokamak devices. His recent work demonstrates how data-driven approaches can enhance control systems for managing transient heat loads and improving reactor stability. As part of major international collaborations including the MAST Upgrade team and TCV tokamak research, Poels contributes to cutting-edge fusion research across multiple institutions. His work appears in high-impact journals including Nature Energy , Communications Physics , and Nuclear Fusion , reflecting the interdisciplinary nature of his research at the intersection of physics, engineering, and computer science.
Caspar A.S. Pouw is a Research Fellow in the Department of Applied Physics and Science Education at Eindhoven University of Technology (TU/e). He holds a dual role as a Postdoc researcher and Data Scientist at ProRail. His work focuses on advancing human crowd flow monitoring, modeling, and nudging technologies, particularly within the HTCrowd project. Pouw’s research integrates fluid dynamics principles to analyze pedestrian behavior in crowded environments, aiming to enhance safety and efficiency in urban spaces. Educated at TU/e, he earned his Master’s in Applied Physics (specializing in Fluids and Flows) and a Bachelor’s in Combustion Science. He has taught courses on sociophysics, covering crowd dynamics analysis, modeling, and nudging strategies. His contributions align with UN Sustainable Development Goals related to safe cities and resilient infrastructure. Recent research emphasizes data-driven modeling of pedestrian dynamics, psychological influences on train boarding efficiency, and real-time monitoring systems. His work bridges physics, computer science, and urban planning, with applications in transportation and public safety. Collaborations include ProRail and interdisciplinary teams at TU/e. Pouw’s datasets and software tools, such as those for pedestrian trajectory analysis, are openly available. His media coverage highlights innovations in crowd management post-COVID-19. Future work involves expanding predictive models for crowd behavior and optimizing transport infrastructure design.
Berend Jan van der Zwaag is an Assistant Professor at Universiteit Twente, affiliated with the Sensors and Smart Systems Research Centre. His work contributes to UN Sustainable Development Goals related to sustainable industry and innovation. He focuses on Artificial Intelligence, Cyber-physical systems, and Machine Learning applications in sensor networks and inertial measurement systems. Research interests include equine gait analysis using IMU sensors, machine health monitoring through ontology-based frameworks, and wireless sensor network design. Notable projects include the EquiMoves system for objective horse gait examination and an ontology framework for smart product-service systems in industrial IoT. Recent work emphasizes terrain classification for equine systems, gait event estimation, and speed estimation using body-mounted sensors. His publications span conferences like IEEE DCOSS-IoT and journals like Sensors and IEEE Internet of Things Journal. Accepting PhD Students Key collaborator: Prof. Paul Havinga (Twente) Research partnerships in Netherlands and international institutions
Ioana Popescu is a prominent hydroinformatics researcher affiliated with the IHE Delft Institute for Water Education , where she has worked since 2001. Previously, she served as an Associate Professor at the Faculty of Hydrotechnics, Timisoara, Romania (1990-1999), and a postdoc researcher at the National Research Council of Canada (2000).
Henk Zijm is a full Professor in the Department of Industrial Engineering & Business Information Systems at the Faculty of Engineering Technology, University of Twente, and is affiliated with the Digital Society Institute. His research spans operations management, logistics, supply chain systems, and stochastic modeling, with a strong focus on practical industrial applications. His research interests include Supply Chain Management , Logistics , Inventory and Spare Parts Control , Multi-Agent Systems , and Digital Transformation in Manufacturing . He has made significant contributions to modeling complex systems under uncertainty, particularly in manufacturing and distribution networks. The 15 most recent articles reflect a consistent focus on supply chain resilience, digital coordination, and sustainable logistics. Key trends include the integration of additive manufacturing in spare parts supply, interactive tools for circular supply chains, and advanced modeling of traffic and production systems. His work bridges theoretical operations research with real-world industrial challenges. Henk Zijm has supervised 24 academic works, indicating active mentorship and PhD guidance. While no specific grants are listed, his extensive publication record and leadership in research areas suggest successful grant acquisition and project leadership. His work has strong interdisciplinary reach, particularly in digital society and systems engineering. He is associated with the Digital Society Institute at the University of Twente, which fosters interdisciplinary research on the societal impact of digital technologies. This affiliation underscores his engagement with broader technological and societal transformations.
Laura Mezzanotte is an Associate Professor in the Department of Radiology & Nuclear Medicine at Erasmus MC, where she conducts cutting-edge research in molecular imaging, bioluminescence, and targeted cancer therapies. Her work bridges pharmacology, oncology, and nanotechnology to develop innovative diagnostic and therapeutic strategies. Her research interests focus on bioluminescence imaging , luciferase-based reporter systems , nanoparticle drug delivery , and photodynamic therapy . She explores applications in glioblastoma , prostate cancer , and immunomodulation , particularly in the context of T cell exhaustion and immune checkpoint inhibition. Her work leverages molecular tools such as aptamers, NIR-dyes, and PSMA-targeted compounds for precision oncology. The recent trend in her publications highlights a strong emphasis on in vivo imaging , combination therapies , and nanocarrier optimization . Her studies integrate preclinical validation with molecular design, aiming to translate imaging and therapeutic innovations into clinical applications. Topics span from antimicrobial implants to dual-color bioluminescence systems for immune monitoring. Scientific Contributions: Developed novel bioluminescent reporter models for immunological studies. Engineered targeted nanoparticles for cancer visualization and treatment. Explored combination therapies involving photodynamic treatment and immunotherapy. Advanced understanding of material-implant interactions in antimicrobial contexts. She has supervised multiple research projects, indicating active mentorship in training the next generation of scientists. Her collaborative network spans immunology, oncology, and materials science, reflecting interdisciplinary research. While no specific awards are listed, her consistent high-impact publications suggest recognition in her field. She leads research in a dynamic lab environment focused on translational molecular imaging and therapeutic development.
Irfan Refai is an Assistant Professor at the University of Twente, leading the HARMONI Lab (Human-Actuated Robotics and Modeling for Occupational and Space Tasks) within the Chair of Neuromuscular Robotics. His research bridges biomechanics, machine learning, and wearable robotics to develop assistive technologies for occupational and space environments. Research Interests: Human-machine interfacing, wearable exosuits, musculoskeletal modeling, sensor fusion, and edge computing for biomechanical applications. Education: Ph.D. in Electrical Engineering (2021), M.Sc. with Research Honors in Electrical Engineering (2017), and B.E. in Biomedical Engineering (2012). Projects: Key contributions to EU-funded SOPHIA and S.W.A.G. projects focused on exoskeleton optimization, fatigue modeling, and industrial applications. Publications: Specializes in EMG-driven models, soft robot design, and minimal-sensor biomechanical systems, with recent work on space-ready exosuits and adaptive assistance algorithms. Leadership: Organizes workshops on digital twins in rehabilitation and industrial exoskeleton challenges; frequently invited to speak at international conferences.
Meng Fang is an Assistant Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology. Their research focuses on artificial intelligence, machine learning, deep reinforcement learning, robotics, and data mining. Key areas include neurosymbolic reasoning, neural network training, and applications in robotics and construction automation. They have received accolades such as the Best Paper Award of LoG 2022 (shared) and were a finalist for the IEEE CASE2021 Best Student Paper Award. Research collaborations span topics like autonomous agents, generalization in reinforcement learning, and benchmark design for AI systems. Meng Fang has supervised 15 academic works and contributed to over 20 research outputs since 2021, with 80 Scopus citations. Their work addresses challenges in level difficulty adaptation, kernel-based neural architectures, and real-time construction planning with robots.
Joris J.C. Remmers is an Associate Professor of Composite Materials at the Department of Mechanical Engineering, Eindhoven University of Technology (TU/e). He is also affiliated with the EAISI High Tech Systems and leads the Mechanics of Materials research group. His academic journey includes a MSc in Aerospace Engineering (TU Delft, 1998) and a PhD in Computational Mechanics (TU Delft, 2006). Remmers' research focuses on composite materials and additive manufacturing, particularly the relationship between manufacturing processes, microstructure, and mechanical properties. He employs advanced numerical techniques to study multi-physics phenomena across scales. Research Themes: Composite materials and fiber-reinforced systems 3D printing and additive manufacturing processes Numerical methods (e.g., finite element analysis, model order reduction) Micromechanical modeling of material behavior Grants and Projects: Project Manager for Innovation test bed for development and production of nanomaterials for lightweight embedded electronics (2019–2023) Awards: Emerging DMD Based Systems and Applications Best Paper Award (2025) Teaching: Leads courses on advanced manufacturing, computational mechanics, and data-driven approaches in engineering, including Advanced and Additive Manufacturing and AI-assisted innovation in portable plasma technology . Labs/Teams: Active in the Mechanics of Materials group, collaborating on multi-scale mechanics, damage modeling, and material failure analysis.
Xiaodong Cheng is an Assistant Professor at the Mathematical and Statistical Methods (Biometris) group in the Department of Plant Science at Wageningen University & Research. His research focuses on control systems, optimization, and machine learning, with applications in agricultural and energy systems. He holds a Ph.D. (cum laude) from the University of Groningen, under Prof. Jacquelien Scherpen, and prior roles include Research Associate at the University of Cambridge and Postdoctoral Researcher at Eindhoven University of Technology. Education: B.S. and M.E. from Northwestern Polytechnical University, China (2011, 2014) Ph.D. (cum laude) in Engineering from the University of Groningen, Netherlands (2018) Research Interests: Data-driven modeling, dimensionality reduction, learning-based control, system identification, and applications in agriculture and energy. He emphasizes practical implementations through tools like SYSDYNET and Bayesian neural ODEs for greenhouse systems. Key Contributions: His work spans model reduction for network systems, fault-tolerant control, and stochastic MPC for greenhouse production. Recent trends in his publications highlight advancements in resilient microgrid control, precision agriculture via drone-based sensing, and Bayesian methods for dynamic systems. Awards: Automatica Paper Prize Award (2017–2019) IEEE Transactions on Control Systems Technology Outstanding Paper Award (2020) Labs/Teams: Leads the Biometris group's efforts in integrating control theory and machine learning for sustainable systems. His work often collaborates with agricultural and energy sector stakeholders for real-world impact.
Dr. Jan Stoop is an Associate Professor in the Department of Behavioural Economics at the Erasmus School of Economics, Erasmus University Rotterdam. His research focuses on measuring social preferences through laboratory and field experiments, as well as designing optimal labor contracts to understand employee incentives and effort. Stoop's primary research interests include the study of social preferences and their real-world applicability, alongside the analysis of labor contracts and employee behavior. He employs a dual methodology of controlled laboratory experiments and field experiments to explore how these preferences and incentives manifest in different settings. Key areas of exploration include unethical behavior in labor markets, gender disparities in academic and professional environments, the effectiveness of information campaigns, and environmental resource management through cooperative frameworks. His recent articles (2013–2025) consistently explore themes of social behavior, labor market dynamics, and experimental methods. Topics include the impact of socioeconomic status on prosocial behavior, disparities in psychological traits and income, and the role of punishment and reward in fostering cooperation. Over time, his work has shifted towards analyzing unethical behavior in digital environments and the broader societal implications of experimental findings. NWO Vidi Grant for applied economist (2019) Stoop advises two PhD students (names not listed) and has secured notable grants, including the NWO Vidi Grant. His research often involves collaborative efforts, combining theoretical models with empirical validation to address challenges in behavioral economics and labor market dynamics.
Hans Butler is a part-time Full Professor in the Control Systems group of the Department of Electrical Engineering at Eindhoven University of Technology. He holds an MSc (1986) and PhD (1990) from Delft University of Technology. As an ASML Fellow, he specializes in dynamics and control systems with a focus on lithographic scanner control, particularly sub-nanometer positioning accuracy challenges. His work integrates physics-guided neural networks and advanced control strategies for mechatronic systems. Research interests include feedforward control design, vibration isolation, opto-mechatronics, and precision engineering applications. His contributions bridge academic research and industrial practice through collaborations with ASML, focusing on high-precision mechatronic systems used in semiconductor manufacturing. Butler has led teams in actuators development, system dynamics, and damping solutions at ASML since 1991. His recent work emphasizes data-driven methods and neural network implementations in control systems, supported by grants like NWO project 17973. He co-developed a MATLAB toolbox for physics-guided neural networks, fostering practical tooling for control engineers.
