Ioannis Athanasiadis is a Full Professor and Chair of Artificial Intelligence at Wageningen University & Research (The Netherlands). He leads the Artificial Intelligence (AIN) group, focusing on advancing AI methods for global challenges in agriculture, ecology, and sustainability. Previously, he was faculty at the Dalle Molle Institute for Artificial Intelligence (IDSIA, Switzerland) and the Democritus University of Thrace (Greece). He holds a PhD (2005, cum laude) in Electrical and Computer Engineering from Aristotle University of Thessaloniki. His research integrates machine learning, knowledge engineering, and environmental modeling to address food security, climate adaptation, and ecosystem services. He leads initiatives like AgML (AgMIP's machine learning benchmarking effort) and coordinates European grants such as LTER-LIFE and CYBELE . Prof. Athanasiadis has supervised over 40 PhD/postdoc researchers and serves as Editor of Environmental Modelling and Software . He collaborates internationally on projects involving AI for crop modeling, digital twins, and sustainable agriculture. His team develops frameworks like Crop2ML and PyCrop2ML to enhance interoperability between process-based models and machine learning systems.
Dr. Jennifer Koch is an Associate Professor at the Laboratory of Geo-information Science and Remote Sensing, part of Wageningen University & Research. Previously, she served as an Associate Professor and Associate Research Director at the University of Oklahoma's Data Institute for Societal Challenges. Her research integrates data-driven methods like simulation modeling to address socio-economic and climate change challenges, focusing on sustainable urbanization and environmental management. Education: She holds a Diplom (Univ.) in Geoecology from the University of Bayreuth and a Dr.-Ing. in Electrical Engineering/Computer Science from the University of Kassel. She teaches courses on geo-information management and data analytics. Research emphasizes multi-scale modeling, stakeholder engagement, and participatory approaches to socio-ecological systems. Recent work explores urban growth in Africa, methane emission monitoring, and renewable energy siting. Articles highlight interdisciplinary methods in GIS, climate policy, and community geography. Professional service includes roles with iEMSs, IALE, and the AAG. No ancillary activities reported. Her work bridges technical geospatial tools with societal challenges, emphasizing practical policy applications.
Achilleas Psyllidis is an Assistant Professor of Urban Mobility and Director of the Urban Analytics Lab at TU Delft. He also leads the Social Urban Data Lab at Amsterdam Institute for Advanced Metropolitan Solutions and is affiliated with the LDE Centre for BOLD Cities. His roles include membership in TU Delft's Transport & Mobility Institute, the Mobility Futures Vision Team, and serving on the Executive Board of CUPUM. Education: PhD in Spatial Data Science (TU Delft, Faculty of Architecture and the Built Environment) Master of Science in Spatial Planning (National Technical University of Athens) Engineering Diploma in Architectural Engineering (National Technical University of Athens) Research Interests: Focuses on accessibility, walkability, land-use dynamics, and travel behavior. Develops computational methods for analyzing access equity, spatial segregation, and human mobility. Leads projects on sustainable urban mobility, environmental exposures, and the 15-minute city concept. Awards: CTwalk Map: Best Demo Award (ICT.Open 2024) ROUTE Ontology of Urban Transportation Entities (2015) Grants & Projects: Involved in initiatives like PERISCOPE (Social Resilience Design), Horizon2020 'Equal-Life' (Environmental Health), and SocialGlass (Urban Analytics Dashboard). Active in research collaborations across Europe and Asia. Labs & Teams: Directs Urban Analytics Lab and Social Urban Data Lab, focusing on data-driven urban solutions. Engages in interdisciplinary teams addressing mobility futures, urban health, and sustainable design.
Dr. Debraj Roy is a Visiting Professor at the University of Amsterdam (UvA), affiliated with the Faculty of Science, Mathematics and Computer Science and the Informatics Institute. His research focuses on agent-based modeling, socio-economic dynamics, environmental resilience, and blockchain technology. He investigates complex systems such as urban slums, disaster recovery, and climate adaptation using computational methods like remote sensing and machine learning. His work bridges theory and practice, offering insights into policy design for sustainable development and social equity. Key research interests include slum dynamics, poverty traps, and the application of blockchain oracles for decentralized systems. He employs advanced techniques such as global sensitivity analysis and manifold learning to explore multi-scale socio-environmental challenges. His recent articles highlight trends in carbon pricing, flood risk valuation, and multi-agent systems. Earlier work concentrated on urban inequality in cities like Bangalore and Mexico City, leveraging geospatial and statistical tools. No scientific awards or grants are explicitly listed. His advising and team collaborations are unspecified in the provided text.
Mila N. Koeva is a Vice Dean Research and senior Associate Professor at the University of Twente's Faculty of Geo-Information Science and Earth Observation (ITC), Department of Urban and Regional Planning and Geo-Information Management. Her research focuses on 3D modeling and Digital Twins for land management and urban planning, integrating geospatial technologies, UAV data, and AI/ML methods. PhD in architectural photogrammetry MSc in Engineering (Geodesy) Research Themes: Digital Twinning for urban ecosystems AI-driven cadastral boundary extraction 3D modeling with LiDAR and satellite data Global partnerships in Rwanda, Kenya, and Ethiopia Interoperability standards for local digital twins Scientific Contributions: Geospatial World Innovation Award 2021 Copernicus Masters Competition (3rd place 2016) Editorial roles in Photogrammetric Records and MDPI journals Keynote speaker at 3D GeoInfo, GI Forum, and FIG events Her educational impact includes developing courses, lecturing, and supervising students whose work has received top awards in The Netherlands and international competitions.
Nina Schwarz is Assistant Professor of human-environment interactions in cities at the Department of Urban and Regional Planning and Geo-Information Management, ITC—University of Twente. Holding a Diploma in Environmental Sciences (University of Lüneburg, 2003) and a PhD in Social and Economic Sciences (University of Kassel, 2007), she spent a decade as senior scientist at the Helmholtz Centre for Environmental Research – UFZ before joining ITC. Her interdisciplinary research integrates urban land-use science, ecosystem-service evaluation and advanced modelling techniques—especially agent-based models—to explore sustainable urban development under global change. Research interests revolve around three interconnected themes: (i) urban land-use change —understanding how residential, commercial and green-space dynamics co-evolve; (ii) urban ecosystem services —quantifying both supply and demand of services such as local climate regulation, recreation and biodiversity; and (iii) behavioural modelling —formalising human decision-making to simulate policy scenarios ranging from slum-upgrading to vineyard management. She actively links these themes to UN Sustainable Development Goals, notably SDG 11 (Sustainable Cities) and SDG 15 (Life on Land). Recent publications (2022-2025) reveal a methodological breadth spanning citizen-science impact assessment in Suriname, cooling effects of urban water bodies in Chinese mega-cities, European wine-growers’ adaptive behaviour, and methodological advances in upscaling and validating agent-based land-use models. Across these studies, Schwarz consistently combines empirical field data, geospatial analytics and participatory approaches to produce policy-relevant insights for cities in both the Global North and South. She has (co-)authored >80 peer-reviewed works, accumulating c. 5 900 citations and an h-index of 28 (Scopus). While specific honours are not itemised in the supplied text, her sustained citation impact and invited contributions to major conferences (e.g., iEMSs 2020, IAHR 2025) underscore scientific recognition. Schwarz frequently engages with societal stakeholders: her projects have generated open datasets on urban green-space monitoring in Paramaribo, e-learning modules for Latin-American universities, and interactive dashboards for sustainable water management. Within ITC she contributes to capacity-building programmes for emerging economies, supervises graduate researchers and maintains active collaborations across Europe, Latin America, Africa and Asia. No explicit lists of PhD students or personal grants are provided in the current corpus, but her leadership of externally funded projects (e.g., citizen-science evaluation, vineyard decision-making database) indicates ongoing acquisition of research funding.
Prof. Dick den Hertog is a Full Professor at Tilburg University's Department of Econometrics and Operations Research, part of the Tilburg School of Economics and Management (TiSEM). His research focuses on operations research methodologies with applications in humanitarian logistics, supply chain optimization, and robust decision-making under uncertainty. He collaborates with organizations like the UN World Food Programme to enhance operational efficiency in complex environments. Key research areas include robust optimization techniques, supply chain management in developing regions, and the integration of satellite data with machine learning for infrastructure analysis. His work addresses challenges such as food aid distribution, disaster response logistics, and predictive modeling for transportation systems in data-scarce areas. Notable projects include developing analytical tools for the WFP's supply chain planning and creating algorithms for weather-informed road speed prediction. He is affiliated with the Tilburg Sustainability Center and the Operations Research research group, contributing to both academic advancements and real-world impact through optimization solutions.
Prof. Suzanne J.M.H. Hulscher is a Full Professor in Water Systems at the University of Twente, specializing in fluvial and coastal morphodynamics. Her research focuses on flood risk management, sediment dynamics, and climate adaptation. She has contributed to over 845 publications and supervised 55 research projects, including Vera van Bergeijk's PhD work on overtopping flows. Key achievements include the Simon Stevin Meester award (2016) and multiple best paper awards. Her work addresses UN Sustainable Development Goals through studies on saltwater intrusion, dike breach modeling, and nature-based solutions. Research highlights include hydraulic model calibration, estuarine sand wave dynamics, and vegetation effects on hydrodynamics. She actively contributes to editorial roles (CivilEng Journal) and policy advisory bodies (Wetenschappelijke Raad). Her interdisciplinary efforts bridge engineering, ecology, and climate science. Research areas: Coastal morphology, river dynamics, environmental hydraulics Key collaborations: 4TU.Centre for Research Data, IAHR, Netherlands Academy of Engineering Grants: Not explicitly listed, but extensive publications imply significant funding Her lab focuses on combining field data with numerical modeling for real-world applications like flood dashboard development and machine learning-based prediction systems. Current projects explore climate change impacts on engineered estuaries and distributive justice in climate policy.
Hans Vernooij is a Lecturer in Farm Animal Health at the Faculty of Veterinary Medicine, Utrecht University. He specializes in statistical methods and data science applications in veterinary epidemiology and animal health. His areas of expertise include: Statistical methods for veterinary research Applied Data Science in Life Sciences Epidemiological modeling Machine learning applications in animal health Vernooij has extensive experience in developing statistical models for animal health applications. His research focuses on applying advanced statistical techniques and data science methods to solve problems in veterinary epidemiology and farm animal health. He has particular expertise in Random Forest models, as demonstrated during his sabbatical at the Human Sciences Research Council in Pretoria where he developed a model for HIV status prediction based on demographic information and knowledge of HIV prevention from large-scale survey data. His publication record shows consistent contributions across veterinary epidemiology, with recent work emphasizing machine learning applications and big data analytics in animal health surveillance. The research demonstrates a clear trajectory from traditional statistical methods toward more advanced data science approaches. Vernooij is actively involved in teaching and mentoring: Teaches statistics to Bachelor students at the veterinary faculty Supports PhD candidates and Master students during data analysis phases of their research Provides statistics education for the Master of Epidemiology program at the Julius Centre of University Medical Centre
Yue Dou is an Assistant Professor in the Department of Natural Resources, focusing on sustainability, land-use dynamics, and food systems. His research addresses UN Sustainable Development Goals, particularly sustainability and food security. He employs advanced modeling techniques and remote sensing to analyze complex socio-ecological systems, emphasizing global-local interactions in agriculture and resource management. Key research interests include crop mapping accuracy in smallholder regions, food value-chain impacts on land use, and resilience in local food systems. His work integrates geospatial data, agent-based modeling, and systems analysis to explore biodiversity conservation, telecoupled systems, and policy implications for sustainable development. Collaborations span global institutions, with recent studies on Jordan’s water-energy-food nexus and Rwanda’s food security monitoring. His publications highlight innovative methods for estimating regional food flows and assessing cropland stability in China. Yue Dou’s contributions address pressing challenges in sustainable land use, agricultural economics, and environmental policy, leveraging interdisciplinary approaches to bridge ecological and socio-economic dimensions.
Hendrik Boogaard is a Researcher at Wageningen University & Research in the Department of Earth Observation and Environmental Informatics. His work focuses on agricultural productivity, remote sensing, and data management, with significant contributions to global crop monitoring systems like WorldCereal and WOFOST. Research Interests : Crop yield modeling, irrigation systems, cropland mapping, data harmonization, and machine learning applications in agriculture. Recent Projects : WorldCereal Reference Data Module, FAIR data guidelines for pig research, and agrometeorological indicator datasets. His publications emphasize improving agricultural forecasting and data infrastructure. He actively participates in workshops and webinars to advance global agriculture monitoring initiatives.
Dr. Irene Manzella is an Associate Professor in the Department of Applied Earth Sciences at the University of Twente. Her research focuses on landslide dynamics, volcanic processes, and granular flow mechanics with applications to natural hazard mitigation. She specializes in experimental geophysics, combining field observations, laboratory simulations, and numerical modeling to understand mass wasting phenomena. Key research areas include debris avalanche propagation mechanisms, sedimentological analysis of volcanic deposits, and the role of particle concentration in gravitational instabilities within volcanic clouds. Manzella's work integrates smart sensor technologies for real-time landslide monitoring and develops innovative methods for disaster impact assessment, such as multi-hazard dashboards and EO-based risk frameworks. Her collaborative projects involve creating flood and earthquake hazard maps for Dominica, developing immersive visualizations for scientific communication, and organizing conferences like the NEEDS conference 2023. Manzella contributes to open-source tools like Python workflows for satellite data processing and has published over 35 peer-reviewed articles in journals like Geomorphology and Frontiers in Earth Science . Recent work emphasizes bidisperse granular flows' scale-dependent behavior, smart sensor applications for tracking debris movement, and improving volcanic hazard predictions through experimental validation of ash cloud dynamics. Her research bridges engineering, geology, and computer science to enhance disaster resilience strategies globally.
Annisa Puspa Kirana is a Ph.D. candidate and researcher at the Department of Geo-information Processing (ITC-GIP), Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente. She is a Lecturer in the Department of Information Technology at State Polytechnic of Malang, currently on study leave to focus on her Ph.D. research. Her work integrates Artificial Intelligence , Computer Vision , and Geospatial Analytics to analyze satellite/aerial imagery for Climate Change Mitigation , Disaster Monitoring , and Resource Management . PhD in Geo-Information Science @ University of Twente (Netherlands) Master of Computer Science @ IPB University (Indonesia) Her research emphasizes Deep Learning applications in Earth Observation, including Vision-Language Models and Agentic AI for multimodal data analysis. She collaborates with interdisciplinary teams , government agencies , and industry partners . Selected Publications Trends: Focus on AI agents , LLMs , VLMs , and Vision Transformers for geospatial and environmental applications Technical tutorials on Streamlit , TalkToEBM , and LangChain integration Conceptual breakdowns of agentic vs. agent-based systems , interpretability in AI , and prompt engineering Scientific Awards: LPDP Awardee (Indonesian Endowment Fund for Education) Microsoft Certified Educator She actively mentors students in AI/geospatial fields and advocates for open-source science and ethical AI practices in environmental decision-making. Her work bridges academic research and practical policy tools .
Michael H. Nagenborg is an Associate Professor in Philosophy specializing in the ethical dimensions of emerging technologies. His research bridges philosophy with practical applications in artificial intelligence, robotics, and geo-intelligence systems. His primary research interests include: Ethical frameworks for AI and robotics Philosophy of technology and empirical philosophy Geo-intelligence ethics and algorithmic fairness Drone data ethics and harm prevention Urban technology ethics and smart city applications Analysis of his recent publications reveals a growing focus on bridging empirical philosophy with design practices, particularly in geo-intelligence and AI ethics. His work increasingly addresses accountability, fairness, and harm prevention in technological applications, with notable contributions to algorithmic fairness through causality and drone data ethics. Dr. Nagenborg has an active research profile with 69 publications since 2004, showing increased productivity in recent years. His work demonstrates strong interdisciplinary connections between philosophy, computer science, and urban studies.
Jeroen Grift is a Researcher in the Department of Earth Observation Science, specializing in geospatial methodologies for cadastral boundary delineation and agricultural monitoring. Earth Observation Remote Sensing Geographic Information Systems (GIS) Land Administration Spatial Data Analysis Geospatial Artificial Intelligence (AI) Grift's recent work focuses on creating benchmark datasets like CadastreVision and AI4SmallFarms . These resources leverage multi-resolution earth observation imagery and deep learning algorithms to address challenges in cadastral mapping and crop field delineation. His research emphasizes improving spatial resolution, accuracy, and automation in geospatial data analysis, with applications for land rights and smallholder farming systems in Southeast Asia.
