Dr. Sander Mann is a Visiting Professor at the Institute of Physics (IoP-WZI), Faculty of Science, University of Amsterdam. His research focuses on quantum optics, nanophotonics, and metasurface engineering. He can be contacted at Science Park 904, 1090 GL Amsterdam, or via email s.mann@uva.nl. His work explores light-matter interactions at the nanoscale, particularly in nonreciprocal systems and topological photonics. Recent publications highlight quantum metasurface design, thermal radiation control, and ultrafast optical switching mechanisms. Using nanophotonic and polaritonic systems, he investigates fundamental limits in optical resonators, nonlinear effects, and energy conversion efficiency. His studies span semiconductor physics, plasmonics, and quantum device engineering.
Heinrich Wörtche is a Professor of Sensors and Smart Systems at Eindhoven University of Technology, leading research in sensor-driven digitization of industrial processes. He holds affiliations including Guest Scientist at the University of Groningen and Senior Researcher roles. His academic career spans positions at institutions like the University of Münster and Rijksuniversiteit Groningen. Education: Doctor rerum naturalium (Nuclear and High Energy Physics), Technical University Darmstadt (1994) Research Interests: Focuses on AI-driven sensor systems, robotics, cyber-physical systems, and industrial digitization. Key areas include visible light communication optimization, autonomous robot localization, and dementia behavior monitoring through sensor technology. His work aligns with UN SDGs for innovation and sustainable industry. Projects: Leads initiatives like MINDD (dementia assistive tech), NXT GEN Autonomous Factory, and XAIPre (explainable AI for maintenance). Active in interdisciplinary collaborations across engineering, healthcare, and AI. Awards: Best Paper Award - OL2A 2023 Grants & Labs: Coordinates EU-funded projects and leads the Sensors and Smart Systems research group. Involved in developing miniature wireless explorative sensor systems and digital twin applications for industrial processes.
Prof. Madeleine Gibescu is a Professor at Utrecht University's Faculty of Geosciences, affiliated with the Copernicus Institute of Sustainable Development in the Department of Energy and Resources. Her research focuses on energy transition pathways, sustainable development, power systems optimization, and renewable energy integration. She leads major projects like WIMBY (Wind in My Backyard) exploring social acceptance of large wind installations and E-Regio developing local energy markets. Her research interests concentrate on developing resilient energy infrastructure, grid modernization, and market mechanisms for renewable integration. She investigates optimization techniques for electricity markets, offshore wind systems, and smart grid technologies with emphasis on SDN-enabled IoT networks and virtualization of grid control systems. Gibescu's recent publications demonstrate strong trends in renewable energy systems optimization, particularly focusing on offshore wind integration, market design for variable renewables, grid resilience, and storage solutions. Her work consistently incorporates advanced computational methods including deep learning forecasting, robust optimization, and virtualization frameworks. She advises PhD candidates including Hsing-Hsuan Chen, Luis Eduardo Ramirez Camargo, and Leanda Vedder on projects related to sustainable energy systems. As principal investigator for Horizon Europe projects, she coordinates interdisciplinary teams developing novel solutions for energy transition challenges.
Vera Dekkers is a researcher and lecturer at Inholland University, affiliated with the Lectorate Power of Sport and Exercise. Her work focuses on fostering inclusion in sports for youth with disabilities, emphasizing policy development, educational material creation, and cross-cultural collaboration. She leads the SEDY2 project, funded by the EU, which aims to enhance inclusion in mainstream sports clubs through shared best practices. Her research spans qualitative studies on youth perspectives, parent insights, and sports professional attitudes across Finland, Lithuania, Portugal, and the Netherlands. Key contributions include the Inclusion Handbook for Sport Clubs , an Educational Material Toolkit for educators, and multi-lingual publications addressing regional challenges. Vera collaborates with international partners to design tools like the Hobby Finder Tool to increase sports participation. Her work bridges theoretical research with practical implementation, advocating for accessible and inclusive sports environments. Publications highlight themes such as digital accessibility, online focus group methodologies, and the impact of mobile apps on health behaviors. She has contributed to neighborhood-based sport initiatives and policy evaluations, demonstrating a commitment to both academic rigor and real-world application.
Gert Kootstra is an Associate Professor in Agricultural Biosystems Engineering at Wageningen University & Research. His research focuses on robotics, computer vision, and machine learning applied to agricultural challenges, including plant phenotyping, UAV path planning, and automated harvesting systems. He leads projects involving 3D plant reconstruction, multi-object tracking in greenhouses, and deep learning for agricultural automation. His work bridges theoretical advancements with practical applications in precision agriculture and autonomous agricultural systems. Education: Not explicitly stated in the text, but his academic rank implies advanced qualifications in agricultural engineering or robotics. Research Interests: Robotics, computer vision, deep learning, UAV-based monitoring, plant phenotyping, and autonomous systems for agriculture. His projects often involve collaboration with industry and other academic institutions to solve real-world agricultural challenges. Recent Trends in Articles: Recent publications emphasize 3D plant segmentation, UAV navigation, and machine learning for object tracking in complex environments. He explores adaptive path planning for drones, automated harvesting techniques using learning from demonstration, and frameworks for uncertainty-aware object assessment in uncontrolled settings. Advising & Grants: Supervises multiple PhD candidates (e.g., Yuan J., Cakaj H., Versmissen T.) in projects funded by grants related to plant phenotyping, UAV applications, and robotics. Collaborates on initiatives like the PicknPack project for automated food processing. Labs & Teams: Involved in robotics and agricultural technology groups at Wageningen, focusing on developing tools for precision agriculture and sustainable farming practices.
Jasper Eikelboom is an academic affiliated with Wageningen University & Research, holding positions in the Wildlife Ecology and Conservation PE&RC and the Laboratory of Geo-information Science and Remote Sensing . His work focuses on applying spatial technologies and ecological modeling to address conservation challenges, particularly in poaching prevention and animal behavior analysis. Eikelboom completed his PhD in 2021, supervised by Prof. Dr. Herbert Prins and others, investigating "Detecting poachers by monitoring animal herd dynamics" . His research interests include wildlife tracking, AI-driven conservation solutions, and the socio-ecological impacts of human activities on animal populations. Notable projects include developing early warning systems using sentinel animal movement data and analyzing the effects of hunting strategies on scavenger populations. Eikelboom has contributed to over 17 peer-reviewed publications, 7 datasets (including movement tracking and poaching detection tools), and 24 media engagements discussing rhino conservation and wildlife policy. Eikelboom’s work bridges ecology, technology, and policy. His datasets (e.g., poacher detection scripts ) and collaborations highlight interdisciplinary approaches to biodiversity protection.
Dr. Shahab Shariat Torbaghan is a tenure-track Assistant Professor of Smart Grids in Urban Energy and Water Systems at Wageningen University & Research. His expertise spans mathematical models, operations research, decision support systems, optimization, stochastic processes, sustainable energy, green infrastructure, machine learning, and energy transition. He holds a B.Sc. in Electrical Engineering from the University of Tehran (2008), an M.Sc. from Chalmers University of Technology (2010), and a Ph.D. from Delft University of Technology (2015). He previously worked as a Postdoctoral Fellow at Eindhoven University of Technology (2015–2017) and as a Research Scientist at VITO/EnergyVille in Belgium (2017–2020). His research focuses on applying sequential decision-making under uncertainty to water and energy infrastructure modeling and optimization, leveraging convex optimization, combinatorial optimization, and machine learning (deep learning, reinforcement learning). He collaborates with the City of Amsterdam, AMS Institute, water companies, and academic partners like HZ University of Applied Sciences and Utrecht University. He participates in European H2020 projects such as Magnitude, FHP, and Coordinate. Dr. Torbaghan teaches courses including 'Sustainability Transitions,' 'Data-Driven Environmental Modelling and Optimization,' and 'Managing Urban Environmental Infrastructure.' His work intersects urban infrastructure transitions, energy storage arbitrage, hydrogen production, and market-based mechanisms for flexibility provision. He is a Senior Member of IEEE and part of INFORMS and the GO-P2P community.
Els van Asselt is an Assistant Professor at Erasmus MC, specializing in neuroscience and urology. Her research focuses on androgen receptor distribution in neural structures (e.g., brainstem, spinal cord) and neuromodulation techniques for bladder and anal sphincter dysfunction. She employs animal models (cats, rats) to investigate mechanisms underlying detrusor overactivity and neuromodulation efficacy. Key research areas include androgen receptor localization in the central nervous system, transcutaneous electrical nerve stimulation (TENS) for bladder control, and discriminant analysis for predicting bladder voiding. Collaborations involve interdisciplinary teams exploring neuromodulation protocols and anatomical pathways. Her work has been published in journals like Journal of Anatomy and Biomedical Signal Processing and Control . While no awards are explicitly listed, her research has garnered citations in peer-reviewed articles and Mendeley readership.
Élise Rouméas is an Assistant Professor in Political Philosophy at the University of Groningen's Campus Fryslân, affiliated with the Global and Local Governance (GLG) department. She serves as Programme Director for the BSc Global Responsibility & Leadership and Interim Head of the GLG Department. Previously, she held postdoctoral positions at the University of Oxford and Sciences Po Paris, with grants including a Horizon 2020 Grant (2019-2020). Her research focuses on compromise in political contexts—particularly religious diversity, digital democracy, and voting ethics—and she co-leads the Democratic Innovation Lab with Davide Grossi. Education: PhD in Political Philosophy from Sciences Po Paris (2016), Fox Fellowship at Yale University (2013-2014), and Alliance visiting scholar at Columbia University (2015). Research explores 'the right to a fair exit' for unattainable compromises, democratic innovations, and ethical voting. Recent work includes AI-driven polling ethics and digital democracy frameworks. Collaborations involve interdisciplinary teams across Europe, addressing topics like trust in governance and participatory mechanisms. Publications include peer-reviewed articles on compromise ethics, digital democracy, and religious accommodation. She contributes to policy debates via platforms like Bij Nader Inzien . Grants include Horizon 2020 funding for voting ethics research. Labs/Teams: Co-leads the Democratic Innovation Lab, collaborating with institutions like Columbia and Sciences Po on digital democracy projects.
Ekaterina Svetlova is an Associate Professor specializing in Financial Engineering, with a strong interdisciplinary focus bridging finance, accounting, behavioral sciences, and science and technology studies. Her research centers on financial technologies, AI ethics, high-frequency trading, and the societal impact of financial modeling. She also explores trust, risk reporting, and open data initiatives across corporations, NGOs, and governmental bodies, including collaborations with HM Treasury. Her research interests include AI ethics in finance , systemic risk , behavioral finance , economic sociology , and governance and accountability . She investigates how financial narratives shape expectations and how digitalization impacts governmental reporting and public trust. The recent trend in her publications (2022–2023) reflects a growing emphasis on ethical and societal dimensions of AI in finance, political communication in corporate disclosures (e.g., Brexit), and critical approaches to accounting education. Her work combines theoretical depth with practical relevance, often engaging with policy and regulatory challenges. She has delivered multiple invited talks on topics such as AI ethics, digitalization in reporting, and accountability, indicating active engagement with academic and policy communities. She has advised on projects related to AI skills development and governmental reporting but no formal students are listed. There are no mentions of specific grants or scientific awards in the provided text. Ekaterina Svetlova is involved in research networks and collaborative projects, particularly around digitalization, accountability, and AI governance, though no formal lab or research center is specified.
Remco W. van der Hofstad is a Full Professor and Chair of Probability at the Department of Mathematics and Computer Science, Eindhoven University of Technology (TU/e). He also serves as Scientific Director of EURANDOM (Dutch center for statistics, probability theory, and stochastic operations research) and co-directs the 'Random Spatial Structures' program at EURANDOM. His research focuses on probability theory, statistics, and their applications to complex networks including social media systems, with specific interests in percolation, random graphs, self-interacting random processes, and interdisciplinary applications in electrical engineering, computer science, and theoretical physics. Key Affiliations: Eindhoven University of Technology (TU/e) EURANDOM Gravitation Program NETWORKS Platform Wiskunde Nederland (spokesman) Research Highlights: He investigates probabilistic models for complex networks, combining theoretical mathematics with real-world applications. His work connects statistical physics concepts (e.g., percolation theory) with network science challenges in areas like glioma patient neuroimaging and pandemic transmission modeling. Scientific Recognition: Recipient of prestigious awards including the Prix Henri Poincaré (2003), Rollo Davidson Prize (2007), and NWO VIDI/VICI grants. His research contributes to UN Sustainable Development Goals related to scientific innovation. Collaborative Leadership: Active in interdisciplinary projects like the Gravitation Program NETWORKS and the Dutch Mathematics Platform. He also contributes to public dissemination through roles as Editor-in-Chief of the Network Pages community website.
Klaas Dijkstra is a Professor of Applied Sciences in Computer Vision & Data Science at NHL Stenden Hogeschool, affiliated with the Academy Technology & Innovation. He holds a PhD from the University of Groningen and leads the Computer Vision & Data Science research group. His roles include co-developer of the master's and minor programs in Computer Vision & Data Science, and chairman of the Cluster Computer Vision Noord-Nederland, a network of over 30 companies. Since 2005, he has led applied research projects in sectors like plastics, agriculture, and microbiology. Notably, he invented a medical device patent and co-authored publications in AI and imaging domains. His work includes developing CentroidNet, a hybrid neural network for object localization and counting. Research focuses on practical applications of computer vision, including medical imaging, agricultural monitoring, and hyperspectral analysis. His work integrates neural networks with real-world challenges, emphasizing interdisciplinary collaboration. Publications highlight advancements in neural network architectures and their applications. Collaborations span industry partners through his role in CCVNN. No specific awards are cited, but his contributions to open-source projects like OpenCentroidNet demonstrate academic impact.
Dr. Sietse van Netten is an Associate Professor at the University of Groningen's Faculty of Science and Engineering, affiliated with the Artificial Intelligence department within the Bernoulli Institute. His research focuses on biophysics, artificial intelligence, and sensor technology, particularly in bio-inspired systems for hydrodynamic sensing and flow analysis. He holds a prominent position in the field of artificial lateral line systems, developing algorithms and sensor platforms for underwater object localization and environmental monitoring. Key research themes include neural network applications for hydrodynamic imaging, multiplexed fiber optic sensors (FBG-based), and biomechanical studies of fish lateral line systems. His work bridges biological principles with engineering solutions, advancing robotics, environmental science, and biomedical applications. Van Netten collaborates internationally on projects involving fluid dynamics, sensor fusion, and machine learning. His contributions span over five decades of publications, emphasizing interdisciplinary approaches to solve complex hydrodynamic and sensory challenges. He currently leads research in sensor array design and bio-inspired systems at the University of Groningen.
Prof. dr. Pieter Jan van der Zaag is a faculty member at the University of Groningen's Zernike Institute for Advanced Materials (ZIAM), leading the Molecular Biophysics group. His research focuses on bionanotechnology, optical imaging techniques for biological tissues, and cancer drug interaction studies. He holds academic positions in both the Faculty of Science and Engineering and the Faculty of Medical Sciences, bridging physics and medical research. Prof. van der Zaag's work includes developing advanced 3D optical imaging methods (e.g., Light Sheet and confocal microscopy) for cancer drug distribution analysis and tissue clearing techniques. His group collaborates with the UMCG and industry partners to translate optical methods into clinical applications like intraoperative imaging. He is active in academic governance, serving as Chairman of NWO's Physics for Technology and Instrumentation committee and co-chair of ESMI's Intra-Operative Imaging study group. His patent portfolio includes innovations in imaging devices, microfluidics, and diagnostic systems. Key research trends in his publications include material characterization for biomedical applications, optical imaging advancements, and single-cell analysis. His work addresses challenges in tissue transparency, drug delivery visualization, and real-time surgical guidance systems.
Dr. Marten van Dijk is a Full Professor in the Computer Security department at Vrije Universiteit Amsterdam (VU) since 2022 and a Group Leader for Computer Security at CWI since 2020. He also holds a Gratis Full Research Professor position at the University of Connecticut's ECE Department since 2020. Previously, he served as Associate and Full Professor at the University of Connecticut and held research roles at MIT CSAIL, RSA Laboratories, and Philips Research. PhD in Mathematics (1997, Eindhoven University of Technology) M.S. in Mathematics (Cum Laude, 1993) M.S. in Computer Science (Cum Laude, 1991) His research focuses on foundational computer security problems using cryptographic principles, including secure processor design, oblivious computation, and privacy-preserving machine learning. Notable contributions span Physical Unclonable Functions (PUFs), Aegis secure processor architecture, and oblivious RAM protocols. 15+ publications in 2023-2025 address topics like PUF cryptanalysis, differential privacy in federated learning, and Byzantine fault tolerance Key journals: IEEE Transactions on Computers, Journal of Cryptology, ACM CCS Conference Award highlights include: IEEE Fellow (2022) for secure processor design and encrypted computation IEEE Technical Achievement Award (2023) Intel Test of Time Award (2022) ACM CCS Best Paper (2013) A. Richard Newton Technical Impact Award (2015) His technical leadership spans hardware security (blu-ray error correction codes), cryptographic protocol design, and machine learning privacy frameworks. Current projects focus on secure processors with hardware-enforced isolation and differential privacy optimization.
