Julia Hertel is a Researcher at the Department of Informatics, University of Hamburg, specializing in Human-Computer Interaction (HCI) and Augmented Reality (AR) systems for industrial applications. Her work bridges AR technology with practical solutions in maritime navigation, hydrographic surveys, and healthcare virtual agents. Bachelor's (2016) and Master's (2020) in Computer Science and HCI from University of Hamburg Her research interests focus on Augmented Reality for industrial contexts , including perception challenges in AR environments, interaction design for immersive systems, and AR tool development for gas station maintenance and maritime navigation. She has contributed to projects like WizARd (2020-2023) and HafenplanZen (since 2022). Julia's publications span AR perception studies, no-code AR authoring tools, and neural rendering for VR. Key collaborations include work on medical virtual agents and geospatial data visualization. She is actively involved in the XR Lab at the University of Hamburg, exploring spatial user interaction and industrial AR applications.
Prof. Dr.-Ing. André Borrmann is an academic leader at the Technical University of Munich (TUM) , where he has headed the Chair of Computing in Civil and Building Engineering since 2011 (formerly Computational Modeling and Simulation). He serves as Director of the TUM Georg Nemetschek Institute - AI for the Built World since 2025 and Spokesperson for the Leonhard Obermeyer Center since 2013. Research Interests Artificial Intelligence in Civil Engineering Digital Twinning Building Information Modeling (BIM) Pedestrian Dynamics Knowledge Representation Construction Simulation His work focuses on AI application across the built environment lifecycle - from generative design to maintenance prediction - with significant contributions to BIM standardization and buildingSMART International IFC extensions. He co-authored the German Ministry of Transport BIM Roadmap and led the BIM4INFRA2020 project. Awards include the 2024 Konrad Zuse Medal and multiple best paper awards at international conferences.
Prof. Monika Sester is a distinguished Professor and Executive Director of the Institute of Cartography and Geoinformatics at Leibniz University Hannover, within the Faculty of Civil Engineering and Geodetic Science. She also serves as Spokesperson for the Leibniz Research Center FZ:GEO and holds multiple leadership roles including Faculty Information Officer (FIO) for the Faculty of Civil Engineering and Geodetic Science, Ombudsman for Good Scientific Practice, and Exchange Coordinator for Geodetic Science and Geoinformatics. Her research focuses on the intersection of geospatial information science, cartography, and urban mobility. Prof. Sester's work spans several key areas: Geospatial data processing and analysis Cartographic representation and visualization Urban mobility and transportation systems Spatial data uncertainty and quality Digital mapping technologies and applications Historical map analysis and interpretation Prof. Sester's recent publications demonstrate a strong focus on applying advanced computational techniques to geospatial problems. Her work shows increasing emphasis on machine learning applications for map analysis, urban mobility optimization, and 3D spatial modeling. She has been particularly active in researching applications of deep learning for historical map interpretation, urban mobility patterns, and spatial uncertainty visualization. Her contributions to the field have been recognized through leadership positions in major research initiatives: Executive Director, Institute of Cartography and Geoinformatics Spokesperson, Leibniz Research Center FZ:GEO Faculty Information Officer, Faculty of Civil Engineering and Geodetic Science Ombudsman for Good Scientific Practice Member of multiple academic committees including the Admissions and Examination Board Prof. Sester actively collaborates with students and researchers across multiple projects focused on geospatial information systems, urban mobility, and cartographic visualization. Her leadership extends to guiding research directions within the Leibniz Research Center FZ:GEO, which brings together interdisciplinary expertise to address complex spatial challenges.
Lukas Pfahlsberger is a scientific collaborator at the Institute of Computer Science , Humboldt University of Berlin, within the Faculty of Mathematics and Natural Sciences. His work focuses on process mining and business process management. Research interests include: Causal process mining and knowledge integration Business process analytics and organizational capability development Big data governance and alignment methods Spatiotemporal analysis in process mining Recent publications explore temporal, multi-perspective, and causal approaches to process mining, with applications in IT demand management and digital transformation. His work bridges technical process mining methods with organizational theory and data governance frameworks. Contact: lukas.pfahlsberger@hu-berlin.de
Shaun J. Grannis is a leading Research Professor at the Regenstrief Institute and Indiana University School of Medicine , specializing in Medical Informatics . His work focuses on patient matching, health data interoperability, and public health surveillance. Research Interests : Patient identification strategies, privacy-preserving record linkage, synthetic data generation, and leveraging health information exchanges (HIE) for population health analytics. Articles : Over 86 publications (2002-2025) addressing real-time disease detection, data quality metrics, and EHR interoperability. Key trends include syndromic surveillance , social determinants of health , and machine learning in clinical data . Awards : Recognized for groundbreaking work in public health informatics and synthetic data applications. Collaborations : Frequent partnerships with institutions like AMIA , JAMIA , and BMC Medical Informatics on projects enhancing healthcare data systems. Grants : Involved in NIH-funded initiatives for national patient-centered research networks.
Prof. Christoph Kinkeldey is a Lecturer at Hamburg University of Applied Sciences, affiliated with the Department of Information, Media and Communication within the Faculty of Design, Media and Information. He holds a doctorate in Geoinformatics from HafenCity University Hamburg (2015) and has conducted research globally, including at PennState University, University of Melbourne, and Inria. His work focuses on data visualization, visual analytics, and uncertainty visualization, emphasizing how visual tools aid decision-making in complex data environments. Education: PhD in Geoinformatics, HafenCity University Hamburg (2015) Research Interests: Interactive visual data analysis Uncertainty communication in visualizations Blockchain data exploration (e.g., Bitcoin network analysis) Evaluation of visualization techniques His research bridges cartography, computer science, and human-centered design to empower diverse stakeholders in understanding complex information. Publications: Recent work emphasizes uncertainty visualization for data analysts, machine learning interpretability, and blockchain analytics. Key contributions include the BitConduite tool for Bitcoin network analysis and participatory design methods for non-technical users. Awards: 2016 VAST Mini Challenge 2: Honorable Mention for Clear Analysis Strategy Advising & Collaboration: Currently on parental leave until August 2024, he collaborates with the gicentre (City, University of London) and Monash University’s Department of Human-Centered Computing. His research teams focus on interdisciplinary projects merging visualization theory with practical applications. Labs/Teams: Active in the gicentre’s visualization initiatives and Monash’s Human-Centered Computing group, contributing to open-source tools and international research networks.
Dr. Guy C. Hembroff is an Associate Professor in the College of Computing at Michigan Technological University, serving as the founding director of the MS in Health Informatics Program and director of the Computational Science & Engineering PhD Program. He leads the Biomedical Data Science (BDS) Lab, focusing on healthcare innovation through AI, cybersecurity, and data science. His expertise spans machine learning, medical image analysis, and healthcare interoperability. Education: PhD in Computational Science & Engineering (Michigan Tech), MPA in Public Administration (Northern Michigan University), BS in Finance and Economics (Michigan Tech). Research interests include human health-focused AI/ML models, cybersecurity in healthcare, medical image segmentation, and public health surveillance. His work emphasizes collaboration with medical institutions like Henry Ford Hospital to develop clinical decision support systems and improve disease surveillance. Recent projects include AI-driven fracture risk prediction from knee radiographs and enhancing mental health intervention efficacy through multi-source data integration. Advising includes four doctoral students in areas like medical image analysis, blockchain for patient data security, and cost-effective mental health modeling. His software projects include FHIR-enabled health information exchange systems and Tick-Talk, a crowdsourced tick disease monitoring platform. Labs/Teams: The BDS Lab integrates expertise in medicine, AI, and cybersecurity to tackle healthcare challenges, emphasizing real-world impact through industry and academic partnerships.
Prof. Dr. Katharina Helming is a Professor leading the Impact Assessment of Land Use Changes working group at the Leibniz Centre for Agricultural Landscape Research (ZALF), affiliated with Research Area 3 on Agricultural Landscape Systems. Her expertise spans interdisciplinary research on land use dynamics, sustainability assessment methodologies, and soil conservation. She holds a Diplom in Agricultural Engineering and a PhD in Agricultural Sciences. Her work focuses on evaluating soil functions, sustainable soil management, and socio-ecological interactions. Key contributions include developing frameworks for sustainability impact assessment and advancing FAIR data infrastructures for agroecosystems. Her research integrates climate change adaptation, digital agriculture, and participatory approaches. Projects include the BonaRes Repository for soil data standardization and protocol-based scenarios for future European agri-food systems (Eur-Agri-SSPs). She leads initiatives on soil health policy and digital transformation in agriculture. Her work emphasizes linking scientific insights with policy through tools like impact mapping frameworks and stakeholder engagement methodologies. Publications highlight innovations in soil data reuse, barriers to sustainable practices, and resilience in community agriculture. She contributes to international initiatives like MACSUR and FAIRagro, addressing global challenges in agri-food systems through interdisciplinary collaboration.
Jayant Madhavan is a researcher at Google specializing in database systems, web data extraction, and information integration. His work primarily focuses on extracting structured data from the web, schema matching, and developing techniques for managing and visualizing large datasets, particularly through projects like Google Fusion Tables and WebTables. Madhavan's research interests center around the challenges of working with web data. His work explores methods for extracting structured information from unstructured web content, particularly focusing on tables and lists. He has made significant contributions to the field of schema matching, developing techniques that enable integration of data from diverse sources. His research also extends to geospatial data processing and visualization, where he has developed algorithms for efficiently handling large geographical datasets for map visualization. His publication record shows a consistent focus on practical applications of database research to web-scale problems. The evolution of his work demonstrates a progression from foundational research on schema matching and data integration to applied work on Google products like Fusion Tables, which enable non-experts to work with structured data. His most recent work examines the ecosystem of structured data on the web and how to effectively extract and utilize this information. Madhavan has collaborated extensively with Alon Y. Halevy (43 co-authored papers) and other researchers at Google, forming a core group that has advanced the state of the art in web data management. His work bridges theoretical database research with practical applications, making significant contributions to both academic literature and real-world data management systems.
Prof. Dr. Jukka Matthias Krisp is a Professor of Applied Geoinformatics at the Institute of Geography, Faculty of Applied Computer Science, University of Augsburg. He leads the Applied Geoinformatics research team focusing on Location Based Services, Geographic Visualization, Spatial Modeling, and GIS applications in ecological network planning. His research interests span multiple domains within geoinformatics: Location Based Services (LBS) including context modeling, navigation systems, and mobile applications Geographic Visualization and Visual Analytics for complex spatial data representation Spatial Modeling techniques for urban environments and transportation systems Geographic Information Systems applications in ecological network planning and environmental monitoring Indoor navigation systems and 3D spatial representation Prof. Krisp's recent publications demonstrate a strong focus on bicycle routing optimization, spatial analysis of social networks, and the integration of AI technologies like ChatGPT for geospatial data generation. His work often combines traditional GIS methodologies with emerging technologies to address urban mobility challenges, traffic congestion analysis, and sustainable transportation planning. He has made significant contributions to the field of Location Based Services, particularly in context-aware computing and spatial data processing. Among his notable scientific contributions: Development of surface roughness-centric approaches to bicycle routing Innovative methods for estimating night populations using mobile network data Integration of big data and cartographic techniques for understanding urban mobility patterns Application of fuzzy inference systems for traffic congestion analysis Narrative approaches to indoor navigation using 360-degree camera documentation Prof. Krisp actively supervises students and collaborates with researchers internationally. His team includes Pablo Löw, Zulfa Nur'aini Afifah, and former members like Lika Zhvania. He teaches courses such as Advanced Spatial Analysis, Geoinformation Systems and Cartography, and Visual Geodata Mining at the University of Augsburg.
Georg Glasze is a Full Professor at the Institute of Geography, Friedrich-Alexander-Universität Erlangen-Nürnberg, leading the Working Group on Cultural/Political/Digital Geographies. His research explores how spaces are (re)produced through socio-technical processes, focusing on discourse theory, digital sovereignty, and geopolitical conflicts. Key Research Areas: Discourse and practice theory in geographies Digital transformation's political implications OpenStreetMap governance and inequalities Smart City critiques and digital governmentality His recent publications analyze European digital policies, environmental crises' spatial dimensions, and contested digital sovereignty frameworks. The working group collaborates with institutions in Canada, France, and Jordan, addressing global challenges through localized case studies. Notable Projects: Resilienz digitaler Infrastrukturen (2024-2028, funded by BMFTR) Offene Geodaten (2024-2026, DFG-funded) Geo-Daten zur digitalen Dokumentation von Menschenrechtsverletzungen (2022-2025, BMFTR)
Gotthard Meinel is a Senior Fellow at the Leibniz Institute of Ecological Urban and Regional Development (IOER) since 2023, with a distinguished career spanning over three decades in geoinformatics and spatial analysis. Previously, he served as Head of the Research Department for Spatial Information and Modeling (2009-2022) and held various leadership positions within the institute since joining in 1992. Meinel received his education at the Technical University of Dresden, graduating in Information Technology in 1981. He pursued postgraduate studies in biomathematics and earned a specialist mathematician degree between 1981-1992, culminating in his promotion (PhD equivalent) in 1987. His research focuses on geoinformatics, particularly remote sensing image processing and the automated analysis of large geospatial datasets. Meinel specializes in monitoring land-use developments and building stock through advanced spatial analysis methods. His work encompasses the development of indicators and visualization technologies for understanding settlement patterns and open space dynamics. With expertise spanning computer science, mathematics, and spatial analysis, Meinel has made significant contributions to the field of land use monitoring in Germany. Analysis of Meinel's recent publications reveals a strong focus on land use monitoring systems, spatial data infrastructure, and the integration of survey and geospatial data. His research increasingly emphasizes interdisciplinary approaches, combining urban planning, environmental science, and data science to address complex spatial challenges. Key trends include the development of comprehensive monitoring frameworks, analysis of building stock characteristics, and exploration of sustainable land use practices across Germany. Meinel has led or participated in numerous significant research projects including the Social-Spatial Research Data Infrastructure (SORA), the Research Database for Non-Residential Buildings (ENOB:DataNWG), OpenGeoEdu, and the Competence Center for Scalable Data Services and Solutions (ScaDS). These projects demonstrate his leadership in developing innovative spatial data infrastructures and analytical approaches. As project leader and principal investigator, Meinel has supervised numerous research initiatives and likely mentored students and junior researchers, though specific advisees are not documented in the provided materials. His work has significantly influenced spatial planning practices and land use monitoring methodologies in Germany. Meinel's research is closely associated with the IOER Monitor, a comprehensive spatio-temporal research data infrastructure for settlement and open space development in Germany. His team has developed sophisticated methodologies for analyzing land use change, building stock dynamics, and urban structure through the integration of topographic data, remote sensing, and statistical approaches.
Colin Ware is a Professor in the Department of Computer Science within the College of Engineering and Physical Sciences at the University of New Hampshire. He directs the Data Visualization Research Laboratory and has established himself as a leading researcher in data and information visualization with a strong focus on the perceptual and cognitive aspects of visual representation. His work bridges computer science, cognitive psychology, and design principles to create more effective visualization techniques. Ware's primary research interests center around how humans perceive visual information and how this knowledge can be applied to create more effective data visualizations. His work spans several key areas including color theory and colormap design, 3D visualization techniques, flow visualization, uncertainty representation, and the cognitive processes involved in visual thinking. He has made significant contributions to understanding how stereoscopic and motion cues affect depth perception in 3D visualizations, and how to design visual representations that align with human perceptual capabilities. Analysis of his recent publications reveals a strong focus on colormap design and evaluation, with numerous papers examining how different color mapping approaches affect feature detection and discrimination. His work increasingly incorporates perceptual modeling and crowdsourced evaluation methods to develop evidence-based visualization design guidelines. He has also maintained a consistent research thread on 3D flow visualization techniques, particularly for scientific applications in oceanography and meteorology. Ware has been instrumental in developing the theoretical foundations of information visualization as a discipline that integrates cognitive science with practical design. His influential book 'Information Visualization: Perception for Design' has become a standard reference in the field, emphasizing the importance of understanding human perception when creating effective visual representations of data. Throughout his career, Ware has mentored numerous graduate students who have gone on to become researchers in visualization and human-computer interaction. His collaborative approach is evident in his extensive publication record, which includes work with researchers across multiple disciplines including oceanography, meteorology, and cognitive science. His laboratory has developed several innovative visualization techniques including the 'Hairy Slices' method for 3D flow visualization, various approaches to representing uncertainty in geospatial data, and novel techniques for designing effective colormaps for scientific visualization. His current research continues to push the boundaries of how we understand and apply perceptual principles to visualization design problems.
Sven Bittenbinder is a Researcher at the University of Siegen , affiliated with the Faculty III (Information Systems and New Media). He contributes to the Department of Information Systems and is a core member of the IT for Ageing Society research group. Education: Diploma in Business Informatics (Wirtschaftsinformatik) from the University of Siegen (2003–2009), with specializations in Data Warehousing, IT Project Management, and System Integration. Research Focus: Bittenbinder specializes in Digital Accessibility , Inclusive Design , and Socio-Technical Systems . His work bridges Human-Computer Interaction and Disability Studies , addressing barriers in workplace accessibility, social service access, and international research collaboration. Recent projects include WERTE.IT (establishing inclusive IT practices) and iDESkmu (accessibility in SMEs). Article Trends: His publications since 2025 emphasize language barriers in citizen science , accessible recruitment/onboarding , and safe spaces for inclusion . Collaborative themes include socio-technical workplace adaptations , community-based participatory methods , and policy-driven accessibility . Projects & Labs: He works in PRAXLABS and Fab Lab Siegen , contributing to initiatives like FUSION , Mittelstand-Digital Zentrum Ländliche Regionen , and WERTE.IT . His focus is on creating inclusive digital infrastructures through participatory research.
Michael Breuer serves as Professor of Photogrammetry and Remote Sensing within Department III – Civil Engineering and Geoinformation at Beuth University of Applied Sciences Berlin. He heads the Photogrammetry Laboratory and maintains extensive professional collaborations with authorities, universities, and companies across Berlin/Brandenburg, Germany, and internationally in geoinformation domains. His research spans photogrammetry, remote sensing, 3D modeling, and geospatial applications for archaeological documentation, disaster response, and environmental monitoring. Key focus areas include: Terrestrial and aerial photogrammetric methods for cultural heritage preservation Satellite-based remote sensing for land cover change analysis Drone-based systems (RPAS/UAS) for emergency response mapping Forensic measurement applications using photogrammetric techniques Integration of AI/ML in geospatial data processing Professor Breuer actively supervises numerous bachelor's and master's theses, often in partnership with external organizations including Brandenburg State Office for Monument Preservation, Berlin Fire Department, GFZ Potsdam, and international archaeological projects. His laboratory maintains strong ties with other BHT facilities including Geomedia Laboratory, Geodetic Measurement Technology Laboratory, and Geodata Analysis and Visualization Laboratory. He teaches core courses in photogrammetry, remote sensing, 3D geodata modeling, and digital image processing across both bachelor's and master's programs in Geoinformation. His teaching emphasizes practical applications through field exercises and industry collaborations.
