Jaap Zevenbergen is a Full Professor at the University of Twente's Faculty of ITC, specializing in Land Administration and Geo-Information Management. He holds a PhD from Delft University of Technology (2002) and degrees in Geodetic Engineering (Delft) and Law (Leiden University). His research focuses on international land governance, digital transformation of property institutions, and pro-poor land tools, with projects in Africa, Southeast Asia, and Eastern Europe. He has contributed to UN Habitat initiatives and World Bank programs, emphasizing sustainable development goals (SDGs 1, 11, 13). Key roles: Theme leader at TU Delft's OTB Institute (2003–2010), Portfolio Manager for MSc Land Administration at ITC. Teaching: MSc programs in Land Administration, GIMA, and International Land Management. Research interests include: Land Administration Domain Model (LADM) implementation, legal-technical integration in geo-ICT systems, and post-disaster/post-conflict land governance. He has authored/co-authored over 340 publications and edited books like Real Property Transactions . Notable achievement: Co-winner of the 2018 FIG-Survey Review Prize for land policy analysis. Current projects explore 3D cadastral systems, UAV applications in land registration, and ethical geospatial practices. He advises on land reforms in Greece and Egypt and collaborates with institutions like UN Habitat and the World Bank.
Samsung Lim serves as an Associate Professor of geographic information systems (GIS) in the School of Civil and Environmental Engineering at the University of New South Wales (UNSW) Sydney. With expertise spanning data science, artificial intelligence, and machine learning, Lim applies geospatial technologies to critical real-world challenges in natural disaster management and public health research. Lim's interdisciplinary work bridges engineering, computer science, and public health domains to develop practical decision-making tools for emergency response and disease surveillance. Ph.D. in Aerospace Engineering and Engineering Mechanics, University of Texas, Austin, TX, USA M.A. in Mathematics, Seoul National University, Seoul, South Korea B.A. in Mathematics, Seoul National University, Seoul, South Korea Lim's research focuses on applying GIS to natural disaster management and public health challenges. Key areas include machine learning methods for bushfire susceptibility mapping, spatial clustering for landslide susceptibility analysis, city-scale evacuation management in flood scenarios, and social media-based natural disaster assessment. In public health, Lim investigates geo-correlations between environmental factors and asthma occurrence, computational approaches to avian influenza outbreaks, emerging hot spot analysis of COVID-19, and early detection systems for emerging infectious diseases. This work combines advanced spatial analytics with machine learning to address complex environmental and health challenges. The recent publication record demonstrates a clear interdisciplinary trajectory where geospatial science intersects with public health emergency response and natural hazard management. Lim's work consistently applies machine learning techniques to geospatial data, with particular emphasis on disaster susceptibility mapping, disease outbreak detection, and infrastructure monitoring. The research spans multiple continents and addresses both immediate emergency response needs and long-term environmental health challenges, reflecting a commitment to practical applications of geospatial science. Associate Editor of Geospatial Information Science National Delegate of Commission 3 of International Federation of Surveyors (FIG) National Representative of the International Cartographic Association (ICA) Commission on Sensor-driven Mapping Senior Member of Institute of Electrical and Electronics Engineers (IEEE) Lim actively contributes to the development of early warning systems for emerging infectious diseases through collaborations with public health researchers. The work on EPIWATCH demonstrates how AI can enhance surveillance capabilities for outbreak detection. Lim's research on cruise ship transmission of diseases and the spread of avian influenza through bird migration patterns and poultry trade networks shows strong engagement with real-world public health challenges. These projects often involve multidisciplinary teams spanning engineering, computer science, epidemiology, and veterinary medicine. Lim's work integrates multiple geospatial data sources and analytical techniques to address complex environmental and public health challenges. This includes developing frameworks for performance analysis of OpenStreetMap data, creating specialized road datasets for pedestrian navigation, and applying Persistent Scatterer Interferometry for land motion monitoring. The research combines traditional geospatial methods with cutting-edge machine learning approaches to extract meaningful insights from complex spatial datasets.
Ajay B. Limaye is an Assistant Professor in the Department of Environmental Sciences at the University of Virginia. His research spans terrestrial and planetary landscapes, focusing on fluvial geomorphology, quantitative stratigraphy, and planetary surface processes. He employs remote sensing, geospatial analysis, numerical modeling, and laboratory experiments to study river dynamics, sedimentary deposits, and climate records on Earth, Mars, and Titan. His work integrates NSF and NASA-funded projects, including the development of a Landscape Evolution Laboratory with a 7m×3m experimental basin for controlled landscape modeling. His research explores feedbacks between landslides and ecology in central Virginia, Martian deltaic deposits, and submarine channel systems. He teaches courses in geomorphology, planetary geology, and fundamental geosciences. NSF CAREER Award (2023) : "GLOW: Sequencing rivers with machine learning and bioinformatics" Keck Institute Fellowship (2010) : High-resolution stratigraphy of Mars polar deposits Recent publications analyze braided river dynamics (e.g., Brahmaputra-Jamuna River), meander bend geometry, landslide-vegetation interactions, and planetary hydrology. His experimental work on autogenic fluvial terraces and turbidity maximum zones in estuaries demonstrates interdisciplinary methodological rigor.
Piotr Jankowski is a Professor of Geography and Director of the Joint Doctoral Program in Geography between San Diego State University (SDSU) and the University of California, Santa Barbara. He holds a Ph.D. from the University of Washington and has held faculty positions at institutions in the U.S., Germany, and Poland. His research focuses on spatial decision support systems, participatory GIS, and sensitivity analysis in spatial models. He has authored/co-authored over 100 peer-reviewed publications and two books on GIS applications in urban planning and decision-making. Education: Ph.D. (1989, University of Washington), M.S. (1979, Poznań University of Economics and Business). Positions include Professor at SDSU since 2003, Director of the Joint Doctoral Program since 2019, and Coordinator of the GIS Certificate Program. He has led international collaborations in Austria, Brazil, Germany, Ireland, Italy, New Zealand, and Poland. Research interests span spatial decision support systems, participatory GIS methodologies, and sensitivity analysis in spatial models. His work emphasizes bridging GIS technology with urban planning and environmental decision-making. Recent publications explore AI-enabled participatory planning, uncertainty in spatial models, and geodiversity assessment. Awards: 2018/19 SDSU Alumni Distinguished Faculty Award. Grants and advising involve spatial optimization, urban sustainability, and environmental modeling. He leads the Center for Earth Systems Analysis Research and has pioneered tools like the Geo-questionnaire for public participation in planning.
Oscar Mendez Maldonado is a Lecturer in Robotics and Artificial Intelligence at the University of Surrey's School of Computer Science and Electronic Engineering, affiliated with the Robotics Department and CVSSP Centre. He holds a PhD (2018) and BEng (2013) from the University of Surrey. His research focuses on Machine Learning, Computer Vision, and Robotics, with emphasis on autonomous systems, localisation, and SLAM applications. Key projects include the Autonomous Valet Parking (AVP) system for indoor navigation and the SMILE project for sign language assessment using AI. He has supervised students like James Ross (Autonomous Vehicles), Xihan Bian (Reinforcement Learning), and Nimet Kaygusuz (Visual Odometry). Notable achievements include the Sullivan Thesis Prize (2018) and impactful publications in IEEE conferences (e.g., ICRA, CVPR, IROS). Research spans topics like 3D hand pose estimation via diffusion models, graph-based visual odometry fusion, and Raman spectroscopy for localisation. He contributes to open-source tools (e.g., RaSpectLoc GitHub) and collaborates with industry partners like Parkopedia. His work bridges theoretical advances with real-world applications in autonomous systems and healthcare.
Özge Öner serves as Associate Professor in Spatial Economics and Real Estate at the University of Cambridge's Department of Land Economy and holds a Fellowship at Sidney Sussex College, where she additionally serves as Vice Master and Director of Studies. Her institutional affiliations extend to research fellowships at Stockholm's Institute of Retail Economics and Jönköping's Centre for Entrepreneurship and Spatial Economics (CEnSE). Her academic foundation includes a 2014 PhD in Economics with specialization in Urban and Regional Economics from Jönköping International Business School, complemented by doctoral research at the University of Illinois' Regional Economics Applications Laboratory (REAL). Prior academic appointments include Assistant Professor at Jönköping International Business School and Researcher at Stockholm's Research Institute of Industrial Economics (IFN). Research Interests: Öner's scholarly work critically examines migration dynamics, labor mobility patterns, micro-geographic segregation mechanisms, ethnic enclave formation, retail/service geography, urban amenity distribution, entrepreneurial geography, and political spatial organization. Her methodological approach heavily leverages geocoded register data and spatial econometric techniques to investigate how geographic context shapes economic behavior, with particular emphasis on Swedish and European urban systems. This interdisciplinary framework bridges spatial economics, economic geography, and migration studies through rigorous quantitative analysis of neighborhood-level phenomena. Publication Trends: Her recent output (2023-2025) demonstrates evolving focus toward infrastructure-impact analysis (tramway effects on commercial vitality), refugee labor market integration pathways, and micro-scale retail/ethnic enclave dynamics. Methodologically, she increasingly employs synthetic control approaches and granular geospatial data to isolate causal mechanisms in urban economic processes, while maintaining strong connections to policy-relevant questions about segregation, integration, and commercial geography. Scientific Awards: Handelsbanken Wallander postdoctoral scholarship (2015) Young Investigator Award in Italy (2018) Young Researcher Award in Sweden (2019) from the Swedish Entrepreneurship Forum Advising and Public Engagement: As Director of Studies at Sidney Sussex College, Öner oversees academic progression for undergraduate students. She actively translates research into public discourse through monthly columns in Svenska Dagbladet (The Swedish Daily News), where she analyzes contemporary socioeconomic issues through her spatial economics lens. While specific doctoral advisees aren't documented in source materials, her leadership roles indicate significant mentoring responsibilities. Research Networks: Öner maintains active collaboration through dual research fellowships: at Stockholm's Handelns Forskninginstitut (Institute of Retail Economics) where she examines commercial geography, and at Jönköping's CEnSE focusing on spatial entrepreneurship patterns. These positions facilitate cross-institutional research on retail dynamics, migration geography, and urban economic structures using Scandinavian longitudinal datasets.
Cantay Caliskan is an Associate Professor at the Goergen Institute for Data Science, University of Rochester. He teaches Data Mining, Statistical Machine Learning, and the Data Science Capstone courses in the undergraduate and graduate data science curriculum. Bachelor of Arts, Brandeis University Master of Arts, Koç University PhD in Political Science, Computer Science, and Statistics, Boston University (2018) His research focuses on computational social science, computer vision, and generative AI, with applications in deep learning, network analysis, and AI ethics in social contexts. His recent publications span interdisciplinary topics including: Geo-cultural bias in AI-generated urban models (SimCityNet) Comparative religious text analysis using LLMs (HalalLLM vs. KosherLLM) Political polarization metrics through social media interactions Article trends highlight AI's role in addressing social science challenges, from electoral geography to disaster response optimization. His work integrates natural language processing, dynamic network modeling, and cross-cultural analysis. He contributes to advancing accessible AI systems (ACROSS) and understanding misinformation dynamics. No scientific awards listed in available data.
Professor Anne Pitcher holds dual appointments as the Joel Samoff Collegiate Professor in Political Science and Afroamerican and African Studies at the University of Michigan. She is also the Associate Chair of the Department of Afroamerican and African Studies and Director of Graduate Studies. Her research focuses on the political economy of urban development, authoritarian governance, and regulatory institutions in Africa, with fieldwork in Mozambique, Angola, South Africa, and Zambia. She serves as President of the African Studies Association and leads projects like the geo-coding of Luanda’s residential developments. Education: Duke University (B.A. Political Science and History), Oxford University (M.Phil. and D.Phil. in Politics). Research Interests: Urban political economy, distribution under authoritarianism, privatization agencies, and comparative party politics. She has built datasets analyzing 29 African countries’ privatization frameworks and is currently studying Luanda and Nairobi’s urban development through a 2018 Stellenbosch Institute fellowship. Awards: Honorable Mention for Best Book (2012), Dudley Seers Prize (2017). She co-edits the African Perspectives book series at the University of Michigan Press. Teaching & Affiliations: Courses include African Politics, Business and Politics in Developing Countries. Affiliated with the Center for Political Studies, African Studies Center, and Program in International and Comparative Studies.
Dr Ritika Tiwari is a Senior Lecturer in Public Health at the York St John University London Campus. She holds over 14 years of experience in public health across South Asia, Africa, and Europe, with prior affiliations to India’s National Health Mission, South Africa’s Stellenbosch University, and the UK’s University of Greenwich. At York St John, she serves as Semester Lead for the MSc Public Health program, leading modules on Health Economics and Public Health for an Ageing Population. Her research focuses on Human Resources for Health (HRH), emphasizing equitable health workforce distribution and universal health coverage. Key areas include geo-spatial inequities in healthcare access, workforce planning models, and policy interventions. Her work has contributed to South Africa’s 2030 HRH Strategy and analyses of dentist shortages, nephrologist deficits, and health workforce trends in India and South Africa. Publications span journals, policy reports (e.g., South African Health Reforms, 2022), and media features on oral health crises and health worker shortages. Dr Tiwari’s academic contributions bridge policy, education, and practice, aiming to strengthen health systems through evidence-based strategies.
Cecilio Angulo Bahón is a full Professor at the Polytechnic University of Catalonia (UPC), affiliated with the Barcelona School of Industrial Engineering (ETSEIB) and the Department of Systems, Automatics and Industrial Informatics Engineering . He leads research in Artificial Intelligence and Robotics , with significant contributions to healthcare data analytics, digital twins, and human-robot collaboration. His research spans machine learning for medical data harmonization, generative adversarial networks in health informatics, and evolutionary algorithms for control systems. Recent publications focus on synthetic healthcare data generation, climate-resilient agriculture , and UMAP-based data analysis . His work bridges AI theory with practical applications in industrial and healthcare domains. Scientific awards include the Sant Jordi 2023 Digital Polytechnic Initiative Award . He has supervised doctoral candidates like Carlos Flores-Vázquez and N. Raya, with key collaborations at the IDEAI-UPC Intelligent Data Science and AI Research Group and the Institute of Robotics and Industrial Informatics (CSIC-UPC).
Qi Chen is a Professor in the Department of Geography at the University of Hawaii at Mānoa, specializing in remote sensing and geospatial technologies. His office is located in Saunders Hall, and he teaches undergraduate and graduate courses including GEO 370 (UAV and Aerial Photography), GEO 388 (Introduction to GIS), GEO 470 (Remote Sensing), GEO 489 (Applied GIS), and GEO 762 (Research Seminar: Remote Sensing. His research focuses on transforming earth observation data into actionable knowledge for environmental monitoring. Primary interests include: LiDAR applications for vegetation analysis and biomass estimation Climate change impacts on land cover and coastal systems Machine learning integration with geospatial data High-resolution mapping of agricultural and forest ecosystems Drone and satellite-based environmental assessment Chen's recent publications (2020-2025) demonstrate a strong focus on advancing remote sensing methodologies, particularly through: AI-driven approaches (GANs for vegetation indices, deep learning for marine debris) Multi-sensor fusion (LiDAR with camera systems, hyperspectral-multispectral integration) Novel applications in precision agriculture and infrastructure monitoring Hawaii-specific environmental studies incorporating indigenous knowledge systems He leads the Smart Remote Sensing Lab (smartremotesensing.org) where he mentors graduate students in developing cutting-edge geospatial solutions for ecological and societal challenges.
Anna Cord is a Professor and Chair of Computational Landscape Ecology at the Technische Universität Dresden, Faculty of Environmental Sciences. She leads research at the intersection of remote sensing, biodiversity, and ecosystem services. Previously, she headed the working group 'Biodiversity and Ecosystem Services' at the Helmholtz Centre for Environmental Research – UFZ from 2012 to 2020. Doctorate (Dr. rer. nat): University of Würzburg, 2012 Studies: Biology and Geography, University of Würzburg and University of Umeå, Sweden Research Assistant: German Aerospace Center (DLR) and University of Würzburg, 2007–2012 Her research focuses on spatial analysis and modeling of land use impacts on biodiversity and ecosystem services , using remote sensing and GIS. She investigates trade-offs and synergies in multifunctional landscapes and develops methods to monitor ecosystem services via Earth observation. Her work supports sustainable land management and policy design. Her recent publications reveal strong trends in ecosystem multifunctionality , multi-objective land use optimization , and integration of socio-environmental data . She emphasizes scalable models, interdisciplinary frameworks, and policy-relevant tools, often using national and global datasets. Her work bridges computational ecology, environmental modeling, and conservation science. Scientific Awards and Honors: Best PhD Student Paper Award, iEMSs Conference, Ottawa, 2010 Scholarship, German Academic Scholarship Foundation, 2004–2007 Member, Young Academy of BBAW and Leopoldina, since 2019 Anna Cord is actively involved in academic service and mentoring. She serves as Study Programme Coordinator for BSc and MSc Geography and teacher training programs at TU Dresden. She leads major research grants such as BESTMAP (EU Horizon 2020) and ECO²SCAPE (BMBF) . She is also an editor for Regional Environmental Change and Remote Sensing in Ecology & Conservation . She contributes to international scientific coordination as Task Leader for Remote Sensing of Ecosystem Services in GEO BON . She has previously served on the Main Committee of the Scientific and Technical Council at UFZ. Her leadership extends to curriculum development and examination boards in geosciences.
Xiaoyang Wang is a Senior Lecturer in the School of Computer Science and Engineering (CSE) at the University of New South Wales (UNSW). He holds a Bachelor's and Master's degree in Computer Science from Northeastern University, China, and earned his PhD from CSE UNSW. Dr. Wang's research focuses on database systems with a special emphasis on query processing and data mining on large-scale graph, spatial, and streaming data. His expertise extends to data-driven machine learning, smart contract analysis on blockchain, and FinTech with financial network analysis. His work spans Graph Processing, Graph Neural Networks, Spatial Data Processing, AI for Databases (AI4DB), Database for AI (DB4AI), and FinTech applications. His publication record shows significant contributions to the field with 7 book chapters, 56 journal articles, 61 conference papers, 7 edited conference proceedings, and 4 conference abstracts. Recent publications (2022-2025) demonstrate his strong research trajectory in advanced graph processing techniques, neural network applications, and innovative database approaches. Key themes include hierarchical contrastive learning, robust attack frameworks, temporal graph processing, influence maximization, knowledge graph-enhanced reasoning, and rumor mitigation. Dr. Wang actively recruits PhD students interested in pursuing research in related fields and encourages current undergraduate and master's students at UNSW to contact him about research opportunities. He maintains an active research agenda with practical implications for industries dealing with large-scale network data, financial technology applications, and data-intensive systems. He can be reached at xiaoyang.wang1@unsw.edu.au and is located in Engineering building K17-501D at UNSW.
Karl Schmid is a W3 Professor of Crop Plant Biodiversity and Breeding Informatics at the University of Hohenheim's Institute of Plant Breeding, Seed Science and Population Genetics within the College of Agricultural Sciences. His research integrates evolutionary genetics, population genomics, and machine learning to address agricultural challenges. Ph.D. in Biology, University of Munich (1996) Postdoctoral Research, Cornell University (1997-1999) Emmy-Noether Research Group, Max Planck Institute of Chemical Ecology (2000-2006) Group Leader, Leibniz Institute of Plant Genetics (2006-2008) Professor of Genetics, Swedish Agricultural University (2008) His research focuses on crop biodiversity conservation, evolutionary genetics of plant pathogens, and breeding informatics applications. Current work leverages deep learning for phenotyping (quinoa panicles, barley genomics) and analyzes pathogen evolution (Exserohilum turcicum in maize). His team actively develops computational tools like GGoutlieR for geo-genetic pattern detection. Recent publications demonstrate strong trends in applying AI to agricultural genomics, particularly in quinoa improvement and pathogen surveillance. His group leads the EU H2020 INVITE project on molecular markers in plant variety protection and organizes international symposia like the 2024 Quinoa Symposium at Hohenheim. Head of Crop Biodiversity and Breeding Informatics Group Principal Investigator, EU H2020 INVITE project Organizer, International Quinoa Symposium 2024
Angelo Corallo is an Associate Professor at the Department of Experimental Medicine, University of Salento, specializing in technologies and methodologies for collaborative processes in industrial systems. His research spans Digital Business Ecosystems , Cybersecurity , and Collaborative Product Design , focusing on the interplay between technology and organizational dynamics. He leads interdisciplinary research divisions in Open Networked Business Management , Learning and Innovation , and Collaborative Product Design . Research Interests : Corallo's work integrates Information and Communication Technologies (ICT) with Business Management, particularly in Digital Twins for healthcare and manufacturing Knowledge Modeling and Ontology Engineering Industry 4.0 and Smart Manufacturing Agri-Food Sustainability through digitalization Scientific Contributions : His recent articles explore trends in Cybersecurity for Industrial IoT Metaverse Applications in business models Traceability Systems in food supply chains Collagen-Based Biomaterials from aquaponics
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