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Prof. Karst Geurs is a Full Professor of Transport Planning at the Department of Civil Engineering and Management, Faculty of Engineering Technology, University of Twente. He chairs the examination board of Civil Engineering and Management and serves as department portfolioholder for education. His research focuses on accessibility analysis, land-use-transport interactions, sustainable mobility, and transport policy evaluation. Geurs holds a PhD (cum laude) from Utrecht University (2006) and has led major projects like the SmartHubs initiative. He is currently vice-chair of NECTAR (Network of European Communications and Transport Activities Research), previously chair from 2014–2024, and served as Editor-in-Chief of the European Transport Research Review (2017–2023). His work addresses cycling safety, mobility hubs, and urban resilience. Key contributions include studies on shared mobility, 15-minute city concepts, and post-pandemic transport trends. He has published over 200 articles and datasets, including work on accessibility equity in São Paulo favelas. Awards include the Gouden RAI Wiel (2015). Geurs actively engages in policy dialogues, media appearances (e.g., Radio 1 interviews), and international conferences. Research interests span transport innovation, spatial equity, and smart infrastructure. Recent projects explore digital mobility skills, teleworking impacts, and cycling safety metrics. His work integrates interdisciplinary approaches to address urban challenges, emphasizing sustainable and equitable mobility solutions.

• Transport Planning
• Sustainable Transport
• Accessibility Analysis
• +5 more

Prof. Sander Bohte is a part-time full professor of Computational Neuroscience at the University of Amsterdam (Swammerdam Institute of Life Sciences) and an honorary full professor of Bio-inspired Neural Networks at the University of Groningen. He serves as a Scientific Staff Member and Group Leader in the Machine Learning department at CWI, Amsterdam. His work bridges computational neuroscience and machine learning with a focus on continuous-time information processing. Key research interests include: Spiking Neural Networks with predictive coding and multi-compartment models Biologically Plausible Learning in recurrent and deep architectures Working Memory modeling via reinforcement learning Neuromorphic Computing for real-time systems and GPU acceleration His recent publications highlight trends in neural adaptation , predictive coding , and SNN hardware-software co-design . Awards include the Veni Innovational Research Grant (2004) and ERCIM grant (2013) . He actively supervises MSc theses and leads grants like the NWO KIC project 'Selfhealing Neuromorphic Systems' (2024).

• Computational Neuroscience
• Machine Learning
• Neural Networks
• +5 more

Hans Bouwmeester is a Full Professor in Toxicology at Wageningen University & Research, specializing in chemical risk assessment, nanomaterial toxicity, and in vitro modeling. His work focuses on integrating artificial intelligence and physiologically based kinetic (PBK) models to predict toxic effects of contaminants like organophosphate pesticides, microplastics, and mycotoxins. He leads projects exploring the health impacts of foodborne contaminants in inflammatory bowel disease and developing animal-free testing methods. Key collaborations include EU initiatives like the ONTOX project and the GUTTEST program, which utilize advanced in vitro models such as gut-on-a-chip systems. Research interests span toxicokinetics, nanoplastics exposure, and the application of Bayesian networks for nanomaterial hazard ranking. His team addresses translational challenges in linking in vitro data to in vivo outcomes, with a focus on bile acid metabolism and cardiotoxicity prediction. Bouwmeester has supervised over 10 PhD candidates, including studies on microplastic hazard assessment, nanomaterial gastrointestinal fate, and AI-driven data extraction for risk assessment. Notable contributions include datasets on nanoplastics' protein corona effects and transcriptomic analyses of intestinal cell responses. His work is published in journals like Ecotoxicology and Environmental Safety , Toxicology , and Environmental Science & Technology , emphasizing open-access research and interdisciplinary approaches to chemical safety.

• Toxicology
• Environmental Toxicology
• Nanomaterial Toxicity
• +3 more

Dr. Asier Moneva is a Postdoctoral Researcher at the Netherlands Institute for the Study of Crime and Law Enforcement (NSCR) and The Hague University of Applied Sciences , specializing in cybercrime , environmental criminology , and situational crime prevention . His work focuses on offender decision-making in cyberspace, cybercrime victimization patterns, and the application of data science to crime analysis. Education : PhD in Criminology (2020), Master in Crime Analysis and Prevention (cum laude, 2017) from Miguel Hernández University. Current Role : Analyzing cybercrime patterns through environmental criminology frameworks and data science methodologies. Moneva's research examines longitudinal offending patterns in cybercrime, particularly through analyses of web defacement archives ( Zone-H data) and hacker behavior. His studies reveal extreme concentration of cybercrime among chronic offenders, with 2.9% of hackers responsible for 68.5% of defacements. He also investigates repeat victimization dynamics in digital environments and the effectiveness of warning banners as deterrents. Recent publications focus on ransomware payment decisions by SMEs, stolen data markets on Telegram, and the intersection of familial relationships with cybercrime involvement. His work combines quasi-experimental designs , crime scripting , and conjunctive analysis to develop prevention strategies.

• Criminology
• Cybercrime
• Environmental Criminology
• +4 more

Yaping Luo is a part-time Assistant Professor at the Mathematics and Computer Science school of Eindhoven University of Technology (TU/e) , Netherlands. She also serves as the Research Lead of the Software Engineering and Automation team at ING Tech R&D since 2018. Her academic journey includes a PhD from TU/e (2016) and MSc/BSc degrees in Computer Science from Beihang University , China. PhD in Computer Science (2016) - Eindhoven University of Technology MSc in Computer Science - Beihang University BSc in Computer Science - Beihang University Her research spans two major domains: automotive safety engineering and software engineering methodologies . She pioneered model-based techniques for functional safety assessment in automotive systems and developed systematic approaches for safety evidence collection and metric design. Her recent work focuses on: Conceptual modeling and meta-modeling Low-code development platforms Business process modeling (BPM) Test automation and model-based testing Her publications demonstrate interdisciplinary applications of: Goal Structuring Notation (GSN) for safety cases Automotive architecture design ISO26262 safety standards Systematic evidence collection frameworks GSN pattern categorization She collaborates across sectors while maintaining her academic affiliation at TU/e.

• Safety Engineering
• Functional Safety in Automotive Domain
• Conceptual Modeling and Meta-Modeling
• +9 more

Joris M. Mooij is a Professor of Mathematical Statistics at the Korteweg-De Vries Institute of the University of Amsterdam, Netherlands. His research focuses on causality, spanning causal modeling, discovery, and inference with applications in biology, medicine, fairness, and business analytics. He combines mathematical modeling with statistical and algorithmic approaches in his work. Dr. Mooij received his PhD with honors from Radboud University Nijmegen in 2007, focusing on approximate inference in graphical models. After postdoctoral work at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany, he obtained an NWO VENI grant in 2011 for further postdoctoral research at Radboud University. He became Assistant Professor at the University of Amsterdam's Informatics Institute in 2013, was promoted to Associate Professor in 2017, and became a full Professor of Mathematical Statistics in 2020. Dr. Mooij's research centers on causal inference, with particular expertise in structural causal models, cyclic causal systems, and causal discovery algorithms. His work addresses fundamental questions about when causal relationships can be identified from observational data and how to develop robust causal discovery methods that work in complex real-world settings with latent variables, cycles, and selection bias. He has made significant contributions to understanding the limitations of existing causal discovery approaches and developing new methods that overcome these limitations. His research group organizes the Amsterdam Causality Meeting series and develops theoretical frameworks for causal modeling that encompass both acyclic and cyclic systems. Dr. Mooij has collaborated extensively on applications of causal methods in biological systems, including protein signaling networks and gene expression data. The group's recent work explores performative predictions, causal domain adaptation, and robust causal discovery methods that account for selection bias and missing data. Dr. Mooij has received numerous awards for his research, including: Best paper award at UAI for "Establishing Markov equivalence in cyclic directed graphs" IEEE Geoscience and Remote Sensing Society 2011 Letters Prize Paper Award ICML Test of Time Honorable Mention Best student paper award at UAI 2010 He has secured competitive research funding through an NWO VENI grant, NWO VIDI grant, and an ERC Starting Grant, which supported the establishment of his research group consisting of 3 PhD students and 3 postdocs focused entirely on causality. Dr. Mooij has supervised several PhD students, including Tineke Blom, whose work on "Causality and Independence in Perfectly Adapted Dynamical Systems" significantly influenced his thinking about causality in complex systems. He has co-taught the MasterMath course on Causality and published lecture notes titled "A Mathematical Introduction to Causality." His research continues to push the boundaries of causal inference methodology and its applications across diverse scientific domains.

• Causality
• Causal Modeling
• Causal Discovery
• +5 more

Julie Legrand is an Assistant Professor in the Mechanical Engineering department at Eindhoven University of Technology , affiliated with the Group Van de Molengraft. Her work focuses on soft robotics , self-healing materials , and medical robotics applications . She designs actuators and sensors for adaptive robotic systems, emphasizing resilience through self-healing mechanisms and embodied intelligence. She teaches courses including Control of a Flexible Robot System , Haptics and Soft Robotics , and Robot-Arm , reflecting her expertise in both theoretical and applied robotics. Her research spans actuator design , material science integration , and minimally invasive surgical robotics , with notable contributions to self-healing actuator validation and continuum robot end-effectors for surgical applications. Legrand collaborates internationally on topics like shape memory alloys and anisotropic materials , and her work has been featured in media for breakthroughs in self-healing polymer limitations in soft robots. She actively contributes to the Medical Robotics research theme at TU/e, advancing interdisciplinary approaches to robotic systems in healthcare.

• Soft Robotics
• Actuators
• Self-Healing Materials
• +4 more

Carlijn Bouten is Full Professor of Cell-Matrix Interactions in Cardiovascular Regeneration at Eindhoven University of Technology. She leads the Soft Tissue Engineering & Mechanobiology group, investigating cellular interactions with extracellular environments in tissue growth, adaptation, and regeneration. Her research develops biodegradable heart valve prostheses that enable in vivo tissue regeneration, applying tissue engineering approaches to cardiovascular medicine. Professor Bouten holds an MSc from Vrije Universiteit Amsterdam and a PhD from TU/e. She completed postdoctoral research at Université Laval and University of London before joining TU/e's faculty. She directs the national Gravitation program 'Materials-Driven Regeneration' and received an ERC Advanced Grant for cardiac tissue organization research. Research Focus: Her interdisciplinary program spans: Mechanobiological cues in tissue regeneration Development of living heart valve replacements Advanced biomaterials for cardiovascular applications In vitro models for tissue development Soft robotic systems for cardiac assistance Recent publications demonstrate innovations in biohybrid devices, standardized biomaterial testing, and novel tissue patterning techniques. Her work integrates engineering, materials science, and clinical translation through collaborations with medtech spin-offs. Leadership and Recognition: Fellow of the European Alliance for Medical and Biological Engineering President-elect of the Heart Valve Society Member of AcademiaNet for Outstanding Female Scientists Recipient of NWO VICI grant and Aspasia award She leads multinational consortia in regenerative medicine and teaches courses on heart/blood physiology and regeneration. Her lab develops model systems spanning cellular to tissue levels to quantify mechanobiological processes.

• Tissue Engineering
• Cardiovascular Regeneration
• Mechanobiology
• +4 more

Marcus Gerhold is an Assistant Professor in the Formal Methods and Tools group at the University of Twente's Faculty of Electrical Engineering, Mathematics and Computer Science. His research focuses on model-based testing for software reliability in critical infrastructures, particularly railway systems, alongside significant contributions to game design and programming language analysis. His educational background includes: PhD in Computer Science from University of Twente (2018): Choice and Chance: Model-based Testing of Stochastic Behaviour MSc in Mathematics from Friedrich Schiller Universität Jena (2013): Embeddings of Weighted Morrey Spaces BSc in Mathematics from Friedrich Schiller Universität Jena (2011): Entropy-, Approximation- and Kolmogorov Numbers on Quasi-Banach Spaces Gerhold's research integrates theoretical model-based testing with practical critical infrastructure applications . His work on railway conformance testing addresses EULYNX controller validation, while his game design research explores affective mirroring in NPCs and procedural dungeon generation. The code modernity analysis stream leverages static analysis to quantify legacy code evolution across languages like Python and PHP, revealing version identification challenges through deep learning. Publication trends show consistent focus on model-based testing methodologies (40%), railway safety applications (25%), and innovative game design/code analysis (35%). Recent work increasingly incorporates AI/ML techniques for UML assessment and Python version identification, while maintaining rigorous formal methods foundations. He actively mentors 63 students across all academic levels and contributes to major research initiatives: STORM_SAFE (ERDF, 2024): Daily Supervisor for WP1/WP2 on software reliability for critical infrastructures ZORRO (KIC grant, 2023): Daily Supervisor for WP4 on zero downtime in cyber-physical systems MISSION (MSCA RISE, 2021-2025): Interim coordinator (early 2024) for space systems modeling As part of the Formal Methods and Tools research group, Gerhold participates in European collaborations while serving on SAC-SVT 2024 and FormaliSE 2023 program committees.

• Model-Based Testing
• Software Reliability
• Critical Infrastructures
• +7 more

Valentijn Visch is a researcher and academic at Delft University of Technology's Faculty of Industrial Design Engineering, specializing in Human-Centered Design and Society, Culture, and Critique. His work focuses on eHealth interventions, gamification in healthcare, and reducing health-related stigmas through innovative design solutions. He teaches courses such as 'eHealth Design for a Healthy Society' and 'Understanding Humans,' emphasizing interdisciplinary approaches to healthcare challenges. His research projects include developing embodied coaches for stroke rehabilitation, AI-driven healthcare decision-making frameworks, and inclusive eHealth tools for low socioeconomic populations. He has been recognized with awards like the Rehabilitation Year Award 2024 for his work on cardiac rehabilitation interventions and a CHI 2024 Best Paper Honourable Mention for studies on patient preferences in AI autonomy. Visch collaborates on initiatives like the 'Emotion Aware Car Seat' project, exploring human-technology interaction. His work bridges academic research with real-world applications, addressing gaps in healthcare accessibility and patient empowerment through technology.

• eHealth Technology
• Gamification in Healthcare
• AI in Medical Decision Making
• +4 more

Dr. Ye Wang is an Assistant Professor at the Department of Microsystems , Mechanical Engineering School , Eindhoven University of Technology . Active in UN Sustainable Development Goals related to biomedical technology, their work focuses on magnetic artificial cilia for microfluidic applications. Academic Rank: Assistant Professor University: Eindhoven University of Technology School: Mechanical Engineering Department: Microsystems Research Interests : Fluid dynamics in microsystems, magnetic actuation, biomechanical stimuli response, and biomedical device development. Key areas include programmable artificial cilia, shear-thinning fluid transport, and biofouling prevention through microscale engineering. Scientific Trends : Recent works emphasize cilia-based microfluidic mixing, non-Newtonian fluid dynamics, and organ-on-chip platforms. Collaborative projects with Prof. J.M.J. den Toonder and P.R. Onck dominate current publications. Advising : Supervised multiple student theses on topics ranging from microrheology to microheater reliability. Graduate students include F.W. Boots , M.H.J. Dekkers , and Y.-T. Lan . Projects : Currently involved in Accelerating Innovation in Microfabricated Medical Devices (2020-2023) with focus on continuous monitoring and advanced diagnostics. Scientific Impact : 1231 citations (Scopus) with collaborative networks spanning fluid dynamics, magnetic actuation, and biomedical applications. Featured in PNAS and Lab on a Chip publications.

• Fluid Dynamics
• Biomedical Engineering
• Microsystems Technology
• +3 more

Prof. Amir A. Zadpoor holds dual roles as Antoni van Leeuwenhoek Professor at TU Delft (Department of Biomechanical Engineering) and Professor of Orthopedics at Leiden University Medical Center. He leads the Additive Manufacturing Lab and specializes in biomaterials, tissue biomechanics, and orthopedic implants. His research focuses on 3D/4D printing, meta-biomaterials, and biodegradable metals for clinical applications. Key research interests include: designing function-tailored implants, antimicrobial biofunctionalized materials, and mechanically adaptive meta-implants. He has pioneered projects like 'Metallic clay' and 'Mechanobiology in-silico,' with applications in orthopedics and regenerative medicine. Notable awards include ERC grants, Vidi/Veni awards, and the Jean Leray Award. His lab develops deployable implants, self-folding origami lattices, and smart meta-implants. Ancillary roles include editorial positions at Springer Nature and directorships at Sylvanity/Zagres. Teaching includes courses on biomaterials, regenerative medicine, and computational biomechanics. Research outputs span over 150 peer-reviewed articles. Current priorities include sustainable biomaterials, AI-driven design optimization, and translating additive manufacturing innovations into clinical practice.

• Biomaterials
• Tissue Biomechanics
• Additive Manufacturing
• +7 more

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.

• Business Process Management
• Data-Driven Process Optimization
• Supply Chain Management
• +3 more

Jop Briët is a Researcher at the Department of Algorithms and Complexity at Centrum Wiskunde & Informatica (CWI) in the Netherlands. His work focuses on theoretical computer science, quantum information theory, combinatorics, and tensor analysis. He has held grants including the Veni Innovational Research Grant from NWO and a Rubicon fellowship. He has authored over 50 publications in leading venues, exploring topics such as Grothendieck inequalities, quantum computing, and additive combinatorics. His research interests span the interplay between combinatorics and computational complexity, with particular emphasis on tensor analysis, probabilistic methods, and algorithm design. Recent work includes studies on Szemerédi’s theorem with random differences and the application of quantum query algorithms to entanglement-based problems. Awards: Outstanding paper award TQC (2020), Andreas Bonn medal (2013), Stieltjesprijs (2011). Professional Activities: Editor for ERCIM News, Board Member of Koninklijk Wiskundig Genootschap, and frequent invited speaker at workshops on quantum computing and combinatorics. Grants: Veni Grant (2014), Rubicon Fellowship (2012). Current teaching includes courses on Additive Combinatorics and Quantum Information Processing, reflecting his commitment to bridging foundational theory with advanced applications in computing and mathematics.

• Theoretical Computer Science
• Quantum Information Theory
• Combinatorics
• +3 more

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

• Learning Analytics
• Human-Technology Interaction
• Artificial Intelligence
• +6 more