Denny Borsboom is Professor in the Psychological Methods Group at the University of Amsterdam, where he directs the Social and Behavioural Data Science Centre. His research program develops network theories of psychopathology, novel psychometric methods, and formalized psychological theory through initiatives like the Psychosystems Project and Theory Methods Lab. Research focuses on conceptual foundations of measurement, complex systems approaches to mental disorders, and computational modeling of psychological phenomena. Recent publications advance network psychometrics, validity theory, and integration of intra/interindividual dynamics. Articles demonstrate strong methodological innovation through computational psychiatry applications, network theory development, and philosophical engagement with psychological foundations. Recurring themes include psychopathological networks, measurement realism, system transitions, and collaborative theory-building frameworks.
Dr. Yara Khaluf is an Assistant Professor in the Information Technology Group at Wageningen University & Research, Department of Social Sciences. She holds a PhD (2014, Paderborn University, cum laude) on robot swarm task allocation, followed by postdoctoral research at Paderborn University (2014–2015) and Ghent University’s IDLab (2015–2021). Her work focuses on computational social science, hybrid human-agent societies, and distributed artificial cognition, leveraging agent-based modeling and systems dynamics for behavior prediction/modulation. She leads European-funded projects like ChronoPilot (EU Horizon2020 FET) and DELICIOS (FWO, 2019–2022). Her research explores interactions between artificial agents and humans, developing cognitive capacities for seamless interaction via social feedback networks. Notable contributions include collective foraging algorithms, time perception modeling, and agent-based simulations for public health interventions. Awards include competitive IGS and DFG fellowships. She collaborates with leading experts in swarm intelligence (Dorigo, Stuetzle), collective decision-making (Hamann, Marshall), and experimental psychology (Johansson, Vatakis). Current projects investigate modulating human time perception and delegation of conflict-of-interest decisions to AI agents. Teaching includes courses on model thinking, agent-based modeling of complex systems, and data science applications in food/consumer science. Her work bridges computational methods with societal challenges, emphasizing scalable solutions for hybrid systems.
Remco M. Dijkman serves as Full Professor in Information Systems at Eindhoven University of Technology (TU/e), chairing the Information Systems group within the Industrial Engineering and Innovation Sciences school. He additionally holds a Full Professor position at EAISI High Tech Systems and acts as research director for high-tech supply chains at the European Supply Chain Forum—a network of over 50 multinational companies. His research centers on Business Process Management with emphasis on data-driven optimization of business processes. His academic background includes both PhD and Master's degrees in Computer Science from the University of Twente. Publications span Information Systems, Computers in Industry, and Transactions on Software Engineering and Methodology, with over 100 papers and service on the editorial board of Information Systems. He has held visiting positions at New York University, Hasso Plattner Institute, IBM Zurich Research Lab, Humboldt-University Berlin, and Queensland University of Technology. Dijkman's research interests focus on detecting, diagnosing, and predicting optimal execution scenarios in business processes, developing mathematical models for quantitative process analysis , and resource assignment optimization . These are primarily applied in transportation logistics and high-tech supply chains, where he investigates data-driven predictions for transport order assignment and supply chain planning. His work bridges artificial intelligence with practical business applications. Recent publications (2024-2025) reveal concentrated efforts in deep reinforcement learning for resource allocation, process pattern discovery, and software library development (GymPN, SimPN). Key trends include predictive process monitoring for healthcare applications, event data enrichment frameworks, and uncertainty handling in logistics planning—demonstrating strong interdisciplinary integration. Scientific recognition includes: Best Demo Award (2019) Best Reviewer Award (2016) Test of Time Award (2019) He has supervised 150 students, including Lotte Vugs who received the Dow Chemical Best OML Master Thesis Award in 2020. Grant leadership spans eight projects: NXTGEN Smart Industry (2023-2030), CollChain (2023-2029), CERTIF-AI (2020-2025), FENIX (2019-2023), and DynaPlex (2021-2024), focusing on digital twins, federated networks, and AI-driven supply chain solutions. Dijkman directs the Information Systems group at TU/e and leads the European Supply Chain Forum's high-tech supply chain research. His work integrates with semiconductor manufacturing and transportation logistics through collaborations with industry partners, while his 2023 invited talks at Technical University of Munich and Humboldt University Berlin highlight his international engagement.
Elisa Perrone is an Assistant Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology. Her research focuses on dependence modeling, copula theory, and their applications in fields such as public transport analysis, environmental risk assessment, and renewable energy forecasting. Academic Rank: Assistant Professor University: Eindhoven University of Technology (TU/e) Department: Mathematics and Computer Science Elisa’s work explores discrete copulas, zero-inflated data, optimal experimental design, and uncertainty quantification. She has contributed to modeling dependence structures in complex datasets, particularly in transportation systems and climate science. Recent research outputs highlight copula-based statistical post-processing for weather forecasts, analysis of multi-way contingency tables, and uncertainty reduction in LED health management. Her publications span top-tier journals and conferences in statistics and applied mathematics. Scientific Award : Second Best Poster Presentation Award (2015) Elisa actively organizes workshops like the Eurandom Workshop on Dependence Modeling and contributes to editorial activities. She teaches courses on linear statistical models, regression models, and dependence modeling.
Frans N. van de Vosse is a full Professor at the Department of Biomedical Engineering , Eindhoven University of Technology. He leads the Cardiovascular Biomechanics research group, focusing on computational and experimental analysis of cardiovascular systems, medical devices, and clinical applications. Academic Background: MSc in Applied Physics (1982), PhD in Numerical Carotid Artery Flow Analysis (1987) from TU/e Professional Affiliations: Full Professor (since 2001), Lecturer in Fluid Mechanics (1987–2001) Research Interests span cardiovascular biomechanics, including Blood in Motion , Heart at Work , and Vessels under Stress . His work emphasizes computational models, experimental techniques, and medical devices for clinical diagnosis and intervention. Key Article Trends include fetal hemodynamics, virtual patient cohorts for coronary disease, abdominal aortic aneurysm progression, and fluid-structure interaction studies in heart valves. Many publications align with UN Sustainable Development Goals related to health and well-being. Media and Public Engagement highlights his contributions to artificial womb technology discussions and clinical device validation studies. His research has been featured in Professional Commentary and PR Activities in cardiovascular engineering.
Dr. Paulien Herder is a Professor at Delft University of Technology (TU Delft) specializing in energy systems, agent-based modeling, and decision-making frameworks. Her work bridges engineering and social sciences through computational simulations. Key research areas: Energy Systems, Values in Engineering, Machine Learning Research Trends: Recent publications focus on agent-based modeling for public health responses (e.g., COVID-19 value dynamics ), machine learning integration in simulations, and community energy system optimization. Her work emphasizes societal impact through interdisciplinary collaborations. Scientific Recognition: Fellow of the Netherlands Academy of Engineering (2023) Academic Contributions: Key publications include critical reviews on community energy initiatives and frameworks for integrating indirect costs in energy planning. Her research output spans over 223 works with significant citations in energy and computational modeling domains.
Gonzalo Nápoles is an Assistant Professor at Tilburg University's School of Humanities and Digital Sciences, Department of Cognitive Science and AI. He holds a Doctoral Degree in Computer Science from Rough Cognitive Networks (2014–2017). His research focuses on AI applications in cognitive modeling, pattern classification, and neural networks with interdisciplinary applications in healthcare, finance, and social sciences. Key research areas include Fuzzy Cognitive Maps, data augmentation techniques for neuroimaging, and interpretable machine learning systems. He actively contributes to UN Sustainable Development Goals related to education and innovation. Recent work explores AI ethics, financial risk assessment using dynamic networks, and sensory processing disorder analysis through neural networks. Education: Doctoral Degree in Computer Science, 2017 (Thesis: Rough Cognitive Networks) Prize-winning research includes Best Paper Awards at CIARP 2021 and IWAIPR 2023. He collaborates internationally, hosting academic visitors and serving on multiple PhD committees. Current projects involve stock prediction using graph neural networks and fMRI data augmentation methodologies. Awards: Best Paper Award - CIARP 2021 Best Paper Award - IWAIPR 2023 Nápoles advises on PhD theses in cognitive science and AI applications. His work bridges theoretical advancements with practical implementations in healthcare, finance, and urban systems.
Han La Poutré is a Professor at Delft University of Technology and a Senior Researcher/Manager at CWI's Intelligent and Autonomous Systems group. His research focuses on multi-agent systems, computational intelligence, and optimization techniques for Smart Energy Systems (SES), integrating electrical engineering and economics frameworks. M.Sc. in Mathematics (1986, TU Eindhoven) Ph.D. in Computer Science (1991, Utrecht University) His work spans game theory , reinforcement learning , and market mechanism design for energy grid optimization, addressing challenges in congestion management, demand-side bidding, and AI-driven media sector innovation. Recent projects include AI, Media & Democracy Lab and RESCUE (Cyber-Physical Energy Security). Key trends in his 2020-2025 publications include: Hybrid fairness/welfare frameworks for grid congestion Double-sided auction mechanisms for heat/power markets Deep reinforcement learning in discrete action spaces Game-theoretical cybersecurity modeling Multi-temporal demand response coordination Scientific Awards 2015: Best paper award at GECCO-2015 He has led NWO-funded projects like Computational Capacity Planning in Electricity Networks and served as Vice President of ERCIM. Current affiliations include ACM Transactions on Intelligent Systems editorial board.
Rianne Conijn is an assistant professor in the Human-Technology Interaction group at Eindhoven University of Technology (TU/e), Netherlands. Her research bridges data-driven methodologies (machine learning, statistical modeling) with human-centered design to enhance learning analytics, explainable AI, and writing process analysis. She holds a joint PhD (cum laude) from Antwerp University and Tilburg University, and an MSc (cum laude) in Human-Technology Interaction from TU/e. Academic Background: MSc (2015, TU/e, cum laude), PhD (2020, Antwerp University & Tilburg University, cum laude). Research Focus: Learning analytics, keystroke logging, explainable AI for education, data dashboards, and self-regulated learning dynamics. Teaching: Courses in Advanced Research Methods, Human-AI Interaction, Behavioral Research Methods, and AI ethics in education. Her recent publications explore parallel language planning in writing, longitudinal self-regulated learning strategies, and generalizability of academic performance prediction models. She leads an NWO Veni project on Human-Centered AI in education, emphasizing tailored explanations for student-AI collaboration. Scientific awards include cum laude distinctions for her MSc and PhD, and the NWO Veni grant. Collaborative work spans institutions in the Netherlands, Norway, and the U.S., with applications in intelligent tutoring systems and ethical AI deployment in exams. Key trends across her work: integration of machine learning with educational theory, leveraging keystroke data for cognitive process insights, and prioritizing actionable, explainable AI systems for student support. Publications span journals like the Journal of Experimental Psychology: General , Computers and Education , and IEEE Transactions on Learning Technologies . Scientific Awards: NWO Veni grant for Human-Centered AI in education Cum laude for MSc and PhD Grants & Collaborations: National Science Foundation grants (2016868, 2302644) for biometric feedback in writing UK Research and Innovation grant (ES/W011832/1) for real-time AI scaffolding TU/e Boost! Program grant for self-regulated learning analysis Labs & Teams: EAISI Foundational (Eindhoven AI Systems Institute) Human Technology Interaction group at TU/e Collaboration with Norwegian Reading National Center (University of Stavanger) Project teams for Waterproof ITS and ProWrite grants
Dr. Jie Li is a dual-career academic and creative professional with a PhD in Industrial Design Engineering from Delft University of Technology. As an HCI/UX researcher in industry and Adjunct Professor at multiple institutions, she bridges academia and practice through work on Extended Reality (XR) , Human-AI interactions , and user experience evaluation . Her ACM Interactions column 'Bits to Bites' explores interdisciplinary research methodologies. Education: MSc in Industrial Design Engineering, Delft University of Technology PhD in Industrial Design Engineering, Delft University of Technology (2019) Her research spans social VR platforms , AI-augmented cognition , and privacy-preserving emotion detection , with recent publications analyzing LLM-assisted game design , harassment detection in VR , and XR's impact on remote collaboration . She has received Best Demo Awards (2020, 2022) and the ACM Best Paper Award (2018). Notable trends in her work include emerging immersive technologies (XR, 6DoF displays), human-AI collaboration frameworks , and cross-domain applications from medical VR clinics to cultural heritage experiences . Her advocacy for synthetic UX research and asynchronous co-creation tools reflects industry-academia hybrid innovation. Scientific Awards: Best Demo Award (2020, ACM TVX/IMX 2020) Best Demo Award (2022, ACM Multimedia) ACM Best Paper Award (2018, ACM TVX) While maintaining active roles in CHI conference committees and guest lecturing , Jie also operates a Delft-based creative cake design business , demonstrating her commitment to interdisciplinary exploration and 'slash career' balance between technical research and artistic practice.
Vera Popovich is a researcher in the Department of Mechanical Engineering at Delft University of Technology and a member of Team Vera Popovich. Her work focuses on advanced manufacturing techniques and material behavior analysis. Education: MSc in Engineering (implied PhD) Her research spans additive manufacturing, microstructure engineering, and material degradation mechanisms: Specializes in additive manufacturing processes and their impact on material microstructure. Investigates hydrogen embrittlement in high-strength steels. Pioneers texture control for corrosion resistance in NiTi alloys. Studies fatigue crack propagation in bi-material systems. Recent publications highlight computational modeling of grain structures, interface mechanics in wire-arc additive manufacturing, and advanced characterization techniques for material degradation. She contributes to editorial activities as an editor for Applied Sciences . Scientific Awards: 2012 Poster Prize: X-ray diffraction stress analysis in silicon solar cells She collaborates on projects like the Rhizome initiative (2021-2022) for off-Earth habitat robotics and participates in public engagement, including a 2023 media feature on Delft's 3D-printing lab.
Marc C.W. Geilen is an Associate Professor at the Electronic Systems group , Eindhoven University of Technology. He leads the Model-Based Design Lab and contributes to the CompSOC Lab and High Tech Systems Center . His work focuses on model-based design methods, design automation, and optimization for real-time and embedded systems. Research Keywords: Cyber-Physical Systems, Real-Time Systems, Embedded Systems, Performance Analysis, Design Automation Key Collaborations: EU ECSEL TRANSACT project, SAM-FMS project, Arrowhead Tools initiative His recent publications address weakly-hard timing constraints in server-based systems, hybrid performance modeling for cyber-physical systems, and neural network optimization for communication. Article trends span Real-Time Scheduling , Trustworthy Modeling , Neural Network Efficiency , and Resource Allocation in distributed environments. Scientific Awards : Partial-Order Reduction for Performance Analysis (2018) Teaching activities include courses in Computational Modeling , Embedded Signal Processing , and Discrete Mathematics . He collaborates across projects like TRANSACT, SAM-FMS, and Arrowhead Tools, focusing on flexible manufacturing and cloud-to-edge transitions.
Didier Meuwly is a Full Professor of Forensic Biometrics at the University of Twente (since 2013) and Principal Scientist at the Netherlands Forensic Institute (NFI). His work focuses on automating and validating probabilistic evaluation of forensic evidence, particularly biometric traces. He has contributed to international standards via ISO Technical Committee 272 and served as Associate Editor for Forensic Science International . PhD in Forensic Speaker Recognition (University of Lausanne, 2000) Research spans forensic biometrics, likelihood ratios, AI validation, and gait/body analysis from surveillance footage. Recent work addresses ISO standards (21043), forensic AI explainability, and multimodal evidence evaluation. His publications emphasize empirical validation and statistical rigor. Key awards include: ENFSI Distinguished Forensic Scientist Award (2022) University of Lausanne Law Faculty Prize (2002) Active in global forensic networks, he chairs the ENFSI R&D Committee and collaborates across disciplines on digital evidence, biometric security, and forensic methodology.
Giulio Dagnino is Associate Professor of Robotics and Mechatronics at the University of Twente and concurrently holds an appointment at the Digital Society Institute. His research integrates medical robotics, real-time perception and haptics to create MR-compatible platforms for endovascular surgery, earning an h-index of 17 and 971+ citations. Education & Career: PhD (details not specified in source) leading to faculty appointment at University of Twente. Promoted to Associate Professor with cross-appointments in Robotics & Mechatronics and Digital Society Institute. Research Interests: Prof. Dagnino’s core interest is medical robotic systems that can operate safely inside an MRI scanner. His work spans haptic guidance, real-time computer vision, soft robotic actuation, synthetic data generation and surgical simulation. By combining ferrofluid actuation, electromagnetic tracking and deep-learning-based scene understanding, he aims to reduce ionizing radiation exposure, enhance navigation accuracy and shorten procedure times for minimally invasive endovascular interventions. Publications Trend: Across 44 outputs (2010-2025) the portfolio reveals a clear evolution from early vision-based microsurgery and fracture-robot systems (2010-2016) toward holistic endovascular platforms integrating MR guidance, haptics and autonomy. Recent 2024-25 papers cluster around (i) synthetic data & scene understanding for surgical AI, (ii) MR-safe robot design and tracking, and (iii) translational studies bringing CathBot and related platforms closer to clinical use. Scientific Awards: Best Design Award – Hamlyn Symposium 2019 (with team) Best Innovation Award – ICRA 2018 Best Paper Award – CURAC 2019 IEEE ICRA Best Paper Award in Medical Robotics – 2016 Grants & Projects: Although explicit grant numbers are not listed, the continuous outputs, patents, multi-institutional collaborations (UK, Germany, Estonia, Canada) and press releases imply sustained funding from EU, Dutch and UK research councils as well as industrial partnerships. Labs & Teams: He leads activities within the Robotics and Mechatronics group at University of Twente, collaborates closely with the Digital Society Institute, and maintains international partnerships visible in co-authored papers with Imperial College London, University of Leeds, and several European hospitals.
David Lentink is a Full Professor of Biomimetics at the University of Groningen , leading the Biomimetics Group within the Faculty of Science and Engineering. His research bridges biomechanics, aerospace engineering, and robotics, focusing on avian flight mechanics and bio-inspired aerial robotics . Previously at Stanford University, he pioneered the development of the Aerodynamic Force Platform and low-turbulence wind tunnels for animal flight studies. Education : PhD in Aerospace Engineering (Stanford), MSc in Mechanical Engineering (Delft), BSc in Mechanical Engineering (Delft). Research Interests : Understanding bird flight biomechanics to design advanced drones, studying evolutionary adaptations in flight, and developing biohybrid robots with real feathers. Scientific Awards : Dutch Academic Year Prize for the Flight Artists (2013). World Economic Forum Young Scientist under 40 (2013). Alumnus of the Young Academy of The Royal Netherlands Academy of Arts and Sciences. Labs : The Lentink Lab at Groningen’s Linnaeusborg campus integrates bird aviaries, wind tunnels, and maker spaces for bio-inspired robotics development. His team collaborates globally with institutions like Stanford, TU/e, and Sorama.
