Niels Batjes is a leading researcher at ISRIC - World Soil Information , specializing in soil data standardization, digital soil mapping, and carbon sequestration modeling. His work focuses on creating harmonized global soil databases like WoSIS and SoilGrids to support climate mitigation and environmental conservation. Key Research Areas : Soil Organic Carbon, Digital Soil Mapping, Pedotransfer Functions, Measurement Error Analysis Projects : Development of soil databases with quantified uncertainties, HoliSoils initiative for European forest soils Recent publications highlight his contributions to global soil water retention modeling, interoperable soil data exchange frameworks, and machine learning applications for carbon stock assessment. He plays a central role in international soil data infrastructure development.
Nandika Tsendbazar is an Assistant Professor at the Department of Geo-information Science and Remote Sensing at Wageningen University & Research. She leads research in land cover mapping, remote sensing applications, and environmental monitoring. Her work focuses on global land cover dynamics, satellite time series analysis, and geospatial data integration for sustainability challenges. Research Interests: Land Cover Mapping & Change Detection Remote Sensing of Ecosystems Drone Technology Integration Urban-Rural Environmental Inequality GIS Applications in Conservation Recent Articles Highlight: Her 2025 study on Peruvian Amazon drone mapping and 2024 global land cover validation work demonstrate her expertise in advancing geospatial techniques for environmental analysis. Ongoing projects include Mongolian grassland resilience and Ramsar wetland monitoring. Advising: Supervises PhD research on tree diversity monitoring, Mongolian grasslands, and crop anomaly detection through remote sensing. Active in 13+ research projects with international collaborators. Labs/Teams: Member of the Laboratory of Geo-information Science and Remote Sensing, contributing to global land cover products like Copernicus and ESA WorldCover initiatives.
Dr. Giorgia Giardina is an Associate Professor in Geo-monitoring and Data Analytics at Delft University of Technology (TU Delft). She holds affiliations with the Department of Geoscience and Engineering, specializing in Geo-engineering. Her research focuses on enhancing urban resilience through the integration of remote sensing, computational modeling, and experimental testing to evaluate structural vulnerability to urbanization, earthquakes, and climate change. She previously held roles at the University of Bath (Lecturer), NASA Jet Propulsion Laboratory (Visiting Professor), and the University of Cambridge (Research Fellow). She is a member of key committees like EEFIT and ISCARSAH. Her work emphasizes heritage protection, seismic retrofitting, and infrastructure resilience. Education & Roles: PhD in Civil Engineering and Geosciences (TU Delft) Leverhulme Early Career Fellowship (University of Cambridge) Research Interests: Giorgia’s expertise spans remote sensing technologies (e.g., InSAR, LiDAR), structural health monitoring, climate change resilience, and disaster risk assessment. She investigates how urban infrastructure and historic buildings respond to subsidence, earthquakes, and underground excavations. Articles & Trends: Recent work emphasizes satellite-based damage assessment (e.g., post-earthquake Turkey 2023, Haiti 2021), InSAR for infrastructure monitoring, and machine learning for crack pattern analysis. Her research highlights the synergy between geospatial data and computational models to improve urban safety. Awards: Leverhulme Early Career Fellowship Grants & Labs: Her group offers fellowships via the Schlumberger Foundation and Mosaic PhD scholarships. Collaborations include the 4TU Centre for Resilience Engineering and the Centre for Global Heritage and Development.
Prof. J.E. Stoter is a leading academic in Urbanism at Delft University of Technology's School of Architecture and the Built Environment. His work focuses on 3D city modeling, geospatial integration, and digital twins. He has contributed to over 378 research outputs and pioneered projects like the nationwide 3D BAG dataset and BIM Legal standards for cadastral registration. Key affiliations: TU Delft, EuroSDR, ISPRS Research interests: Urban data infrastructure, BIM-GIS integration, digital twin applications Notable achievements include the Geospatial World Excellence Award (2021) and foundational work in CityGML standards. His research spans energy modeling, solar simulation, and urban policy frameworks, with significant contributions to automated building reconstruction from LiDAR data. Recent articles explore solar simulation tools, lane mapping benchmarks, and urban digital twin challenges. His work bridges geospatial science with practical urban planning applications, emphasizing interoperability and sustainability.
Tabea Sonnenschein is a Researcher at Utrecht University , affiliated with the Faculty of Geosciences and Human Geography and Spatial Planning . She is also a PhD Candidate in the Department of Population Health Sciences under the Faculty of Veterinary Medicine . Her work bridges environmental science, urban planning, and public health through advanced computational modeling. Coordinated EU-funded EXPANSE (Horizon 2020) and EXPOSOME-NL (NWO) projects. Research Associate at the MRC Epidemiology Unit at University of Cambridge, contributing to DARe Hub and UBD Policy initiatives. Research Interests Air Pollution and Health: Modeling health impacts of urban pollutants. Agent-Based Simulation: Developing tools like GenSynthPop and CellAutDisp . Urban Sustainability: Assessing interventions for resilient, low-emission cities. Recent Publications highlight her work on urban exposome, synthetic population modeling, and subway expansion impacts. She contributes to journals like Environmental Modeling and Software , Autonomous Agents and Multi-Agent Systems , and Semantic Web .
Patrick Forré is an Assistant Professor and Lab Manager of the AI4Science Lab at the Informatics Institute, Faculty of Science, University of Amsterdam. His work bridges theoretical machine learning and scientific applications, fostering interdisciplinary collaboration across informatics, mathematics, ecology, chemistry, physics, biology, and astrophysics. His research centers on mathematical foundations of machine learning including causal inference, graphical models, information theory, conditional independence structures, and geometric deep learning. He specializes in applying these techniques to scientific data problems, particularly in electro-catalysis and nitrogen fixation, where machine learning enhances molecular simulations and quantum chemical modeling. His theoretical work addresses non-linear structural causal models with cycles and latent confounders. The AI4Science Lab under his management focuses on detecting hidden patterns in scientific data through projects like electrode-electrolyte interface modeling, nitrogen-fixing coordination complexes analysis, and classical DFT neural approximations. Located in LAB42 Building at Amsterdam Science Park, the lab connects diverse scientific disciplines through machine learning innovation while organizing colloquia, workshops, and PhD defenses.
Tina Comes is a Researcher at the Department of Technology, Policy and Management , Delft University of Technology , with a focus on Transport and Logistics . Her work integrates Decision Theory , Resilience Engineering , and Artificial Intelligence to address complex challenges in Disaster Management and Humanitarian Logistics . 2025: Agent-Based Modeling for crisis adaptation 2025: HILP Event Taxonomy for risk classification 2024: Dynamic Bayesian Networks in emergency mapping Her research combines Computer Science and Urban Planning to develop Data-Driven Decision Support Systems , with recent studies on flood response , healthcare resilience , and ethical AI . She has contributed to 70+ research outputs and supervised interdisciplinary projects like 4TU Resilience Engineering Centrum initiatives. Selected Trends: Prior work emphasizes information asymmetries , cognitive biases , and multi-modal data in crisis scenarios. She actively explores spatio-temporal analytics and blockchain applications for humanitarian coordination. Key Collaborations: Partnerships with European Safety and Reliability Conference (2020), ISCRAM Conference (2025), and Kenyan Election Fact-Finding (2018) Press Mentions: Highlighted in AI for Mobility (2025) and 4TU Resilience Centrum Launch (2018)
Dr. Serkan Girgin is an Associate Professor at the Department of Geo-information Processing, Faculty of Geo-Information Science and Earth Observation, University of Twente. He leads the Center of Expertise in Big Geodata (CRIB) and contributes to global initiatives in geospatial big data, cloud computing, and disaster risk assessment. His work bridges academic, private, and scientific sectors with over two decades of experience since 1996. M.Sc. and Ph.D. in Environmental Engineering Second M.Sc. in Geodetic and Geographic Information Technologies Research interests span geospatial data science, machine learning for remote sensing, open science frameworks, and Natech risk assessment. He has designed systems like ITC's Geospatial Computing Platform, eNatech Database, and RAPID-N for risk mapping. Recent publications focus on digital twins for soil-plant systems, SAR benchmark datasets, and automated workflows for Sentinel-1 interferometry. His projects include ESA EO AFRICA R&D Facility, SURF's Next Generation Data Repositories, and Netherlands eScience Centre's EcoExtreML. eScience Center Fellow (2022) SURF Research Support Champion (2022) Multiple early-career awards in programming (1993-1996) and thesis excellence (2005) He actively develops tools for citizen science (e.g., QGIS Light) and advocates for FAIR data management. His collaborations extend to Zenodo datasets and international conferences on geospatial resilience.
Karin Pfeffer is a Full Professor at the Department of Urban and Regional Planning and Geo-Information Management within the Faculty of Geo-Information Science and Earth Observation at the University of Twente. Previously, she served as Associate Professor at the University of Amsterdam (2009-2016) and as Vice-Dean Research at ITC (2020-2024). Her work bridges geospatial technologies with urban sustainability, focusing on infrastructure, equity, and digital innovation. PhD in Physical Geography, Utrecht University Research Interests: Urban infrastructures, socio-spatial inequality, digital twins, participatory GIS, and climate-resilient urbanism. She integrates GIS, remote sensing, and qualitative methods to analyze urban poverty, smart cities, and nature-based solutions. Recent Article Trends: Her 2024-2025 work examines remote work's urban-rural impacts , inclusive mapping tools , and digital twins for drainage systems . Themes span geospatial analytics, equity in infrastructure, and collaborative planning. Scientific Awards: 2022-23: Room for Failure in Science Grant (Diversity, Equity & Inclusion Fund) Supervised Work & Grants: She guides 12 ongoing and 23 completed PhD projects (e.g., urban mobility in Saudi Arabia, digital twins for drainage systems). Past projects include DynaSlum (slum growth modelling) and CODALoop (energy behavior feedback). Her research aligns with UN SDGs 11 (Sustainable Cities) and 13 (Climate Action).
Bettina Speckmann is a full Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU Eindhoven), where she leads the Applied Geometric Algorithms group. She holds additional appointments as EAISI Health Professor and EAISI Foundational Professor, and is affiliated with the Data Science Center Eindhoven. Her research bridges theoretical algorithm design with practical applications in spatial computing. Her research interests lie primarily in computational geometry and geometric algorithms, with strong applications in GIScience, Smart Mobility (including moving object analysis and automated cartography), geo-visualization, visual analytics, and e-Humanities. She focuses on developing efficient algorithms and data structures for spatial data, combining rigorous theoretical methods with practical engineering for real-world impact. Her recent publications (2025) show a strong trend in geometric data processing, particularly in polycube segmentations, dual loop algorithms, density estimation for moving groups, and topological analysis using merge trees and Fréchet distances. These works reflect her interdisciplinary focus on computational geometry, visualization, and data structures. Scientific awards received include: Netherlands Prize for ICT Research (2011) NWO Vici Award (2012) PEriTiA Prize (2020) Bettina Speckmann has advised numerous students and researchers through her group and has secured major grants, including the NWO Vici. She has served in leadership roles such as PC co-chair for Graph Drawing (GD 2011), PC chair for ICALP Track A (2015), and PC co-chair for SoCG (2018). She teaches courses such as Data Structures and Heuristic Algorithms. She leads the Applied Geometric Algorithms group, which actively collaborates with industry partners like HERE Global B.V., Fugro NL Land B.V., and OCLC B.V., and contributes to UN Sustainable Development Goals in areas related to data and mobility.
Luc Steinbuch is a Research Associate at Wageningen University & Research specializing in Geostatistics and Digital Soil Mapping . His work bridges Bayesian statistical frameworks with environmental science applications. Key Research Areas: Geostatistical modeling, luminescence detection, AI in academia, sustainability education Notable Projects: Bayesian geostatistics for soil mapping (2014-2021), crosstalk analysis in luminescence data (2025), AI implications for academic work (2023 keynote) Recent publications demonstrate methodological innovations in Geoderma (2024) and Radiation Measurements (2025), focusing on improving spatial data accuracy through machine learning and Bayesian approaches. His work impacts both fundamental scientific understanding and educational practices in soil science. As a contributor to open-source software development, Steinbuch has created tools for luminescence data analysis. He actively engages in academic communication, evidenced by his 2023 media spotlight and 2025 Zenodo report on sustainability education.
Irene van den Broek is an Assistant Professor at the College of Pharmaceutical Sciences , Utrecht University , within the Chemical Biology and Drug Discovery department. She combines academic roles with freelance data visualization work. Teaches Bioanalysis (Bachelor's level) Supervises students in academic writing and intervision Develops interactive R Shiny applications for citizen science projects Her research focuses on: Bioanalysis techniques Quantified Self health tracking Data Visualization for health & environmental data Wearable Devices integration (Ōura Ring, RescueTime) Key article trends include environmental monitoring ( Onze Lucht , Was het Donker? ) and personal health analytics using R packages like echarts4r and reactable . Projects emphasize interactive web visualization and citizen science applications. She provides: Academic writing guidance Tutoring frameworks for student intervision Workshops on scientific communication Key projects include: Onze Lucht (air quality heatmaps) Was het Donker? (light pollution visualization) Ōura Ring Analysis (sleep/activity metrics)
Dr. Timothy Tiggeloven is a Researcher at the Institute for Environmental Studies (IVM) within the Faculty of Science at Vrije Universiteit Amsterdam, specializing in Water & Climate Risk since 2017. His postdoctoral research, funded by the MYRIAD-EU project, focuses on multi-hazard risk management and social vulnerability, aiming to enhance disaster resilience. He holds a PhD (2022), MSc (2017), and BSc (2015) in Earth Science & Economics from VU Amsterdam. PhD: Coastal Flood Risk and Nature-Based Solutions MSc: Hydrology BSc: Earth Science & Economics Research interests include climate change adaptation, flood risk assessment, and the integration of nature-based solutions. His work addresses coastal flood mitigation, multi-hazard dynamics, and vulnerable communities' resilience. Notable projects include analyzing global flood risk reduction through vegetation conservation and leveraging AI for multi-risk assessment in Europe. Key articles explore inclusive disaster risk reduction for marginalized groups, storm surge predictions using neural networks, and mangrove conservation's role in coastal protection. His contributions to datasets like Climate Risk STAC advance geospatial data for climate risk assessments. Funded by MYRIAD-EU, his research bridges policy and science to address complex climate hazards. He collaborates on global hazard datasets (MYRIAD-HES) and teaches 'Measuring Techniques in Hydrology.'
Yuri Engelhardt is an Assistant Professor at the Faculty of Geo-Information Science and Earth Observation within the University of Twente , specializing in the Department of Geo-information Processing . His work bridges visualization, geography, and sustainability science. As a visualization expert, Yuri focuses on creating equitable visual communication tools that address climate crisis , health , and biodiversity challenges, aligning with UN Sustainable Development Goals. He explores diagrammatic representation and alternative visualization options for practical design applications. His research output demonstrates cross-disciplinary collaboration spanning computer science, geographic information systems, and visual communication. Notable work includes systematic approaches to visualization classification and map design innovations that leverage spatial metaphors.
Erkut Akdag is a postdoctoral researcher at the Department of Electrical Engineering, Eindhoven University of Technology, specializing in artificial intelligence for smart city surveillance and transportation systems. He contributes to projects focused on anomaly detection, urban mobility optimization, and multi-modal sensing. Academic Rank: Researcher Contact: e.akdag@tue.nl His research addresses UN Sustainable Development Goals related to sustainable cities (SDG 11) and infrastructure (SDG 9). Key interests include Anomaly Detection , Smart City Surveillance , and Intelligent Transportation Systems . Recent publications emphasize anomaly detection in surveillance videos, distracted driver action recognition, and geo-spatial traffic analysis. His work leverages deep learning , temporal attention mechanisms , and spatio-temporal embeddings . Scientific recognition includes the Award for Exceptional Excellence (ITEA 2024) for collaborative research projects. He actively presents at international conferences, including IEEE VCIP and ICMV.
