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Konrad SchindlerView profile

Professor

• Photogrammetry
• Remote Sensing
• Computer Vision
• +3 more

Prof. Konrad Schindler holds the position of Full Professor at the Department of Civil, Environmental and Geomatic Engineering at ETH Zürich. He is also the Head of the Institute of Geodesy and Photogrammetry (IGP), leading research and educational activities in geomatics and computer vision. His career spans roles as a Photogrammetric Engineer, scientific assistant, postdoc researcher, and academic faculty across institutions including Graz University of Technology, Monash University, and TU Darmstadt before joining ETH Zürich in 2010. Education: Undergraduate studies in Geodesy (1992–1995), Graz University of Technology, Austria MEng in Photogrammetry and Geoinformation (1995–1999), Vienna University of Technology, Austria PhD in Computer Science (2001–2003), Graz University of Technology, Austria Research focuses on Photogrammetry , Remote Sensing , Computer Vision , and Image Understanding with interdisciplinary applications in environmental monitoring, geospatial analysis, and disaster response. He develops computational methods for 3D reconstruction, fusion of multi-modal data, and AI-driven solutions for satellite imagery interpretation. His work bridges geomatic engineering and machine learning to address challenges in urban mapping, climate modeling, and biological systems analysis. Publications reflect expertise in geospatial AI, diffusion models, and benchmarking datasets for disaster resilience. Notable works include Marigold (image analysis adaptation) and BRIGHT (building damage assessment). His research emphasizes practicality and scalability, such as affordable depth estimation and global biomass datasets. He has received the 2013 Marr Prize Honourable Mention (IEEE) and the 2012 U.V. Helava Award (ISPRS), alongside several Best Presentation Awards. His contributions span technical leadership, editorial roles (ISPRS Journal), and service to Swiss remote sensing commissions. Advising and grants: While no specific advisee names or grant details are listed, his career trajectory includes mentoring postdocs and junior faculty. He teaches advanced courses in Photogrammetry , Image Interpretation , and Machine Vision , integrating cutting-edge AI techniques into curricula. His research group collaborates on global-scale projects like canopy height mapping and satellite-based climate variable assessments. Labs/Teams: As Institute Head, he oversees the IGP lab at ETH Zürich, with prior affiliations including the Digital Perception Lab (Monash University) and the Computer Vision Lab (ETH Zurich). His work often involves multi-institutional collaborations focused on geospatial AI and environmental science.

• Carbon Cycle
• Climate Science
• Biogeochemistry
• +6 more

Prof. Dr. Ana Bastos is a Research Professor and Group Leader at the Max Planck Institute for Biogeochemistry (MPI-BGC) in Germany, affiliated with Leipzig University's Institute for Earth System Science and Remote Sensing. She holds a PhD in Geophysical and Geoinformation Science (2015, U. Lisbon) and a BSc+MSc in Environment and Energy Engineering (2011, U. Lisbon). Her research bridges atmospheric science, ecology, and biogeochemistry to study carbon-cycle dynamics, climate extremes, and ecosystem disturbances. She leads major projects such as the ERC Starting Grant-funded ForExD initiative and contributes to global carbon cycle assessments like RECCAP-2. Key roles include membership in the World Climate Research Programme's Safe Landing Climates initiative and leadership in the ICOS-RI Drought Task Force. She has over 40 international conference presentations and organizes sessions at AGU and EGU meetings. Her awards include the EGU Outstanding Early Career Scientist Award (2022) and the Beutenberg Campus Award (2021). She actively mentors early-career researchers through PhD and postdoc programs focused on forest disturbance modeling and remote sensing applications.

• Photogrammetry
• Geoinformation
• Remote Sensing
• +7 more

Prof. Christian Heipke is a distinguished academic serving as Dean of the Faculty of Civil Engineering and Geodetic Science at Leibniz University Hannover, Germany. He also holds the position of Executive Director at the Institute of Photogrammetry and GeoInformation (IPI), one of the leading research institutions in geospatial sciences within the faculty. His leadership extends across multiple committees including the Curriculum and Teaching Committee, Admissions and Examination Boards for Geodetic Science and Geoinformatics, and Navigation and Environmental Robotics. As a Professor at IPI, he maintains active research while overseeing significant academic and administrative responsibilities at the university. Professor Heipke's research spans multiple domains within geospatial sciences, with particular emphasis on: Advanced photogrammetric techniques and algorithms Remote sensing applications for environmental monitoring Computer vision approaches for geospatial data analysis Urban development monitoring using satellite imagery Machine learning applications in geoinformatics Disaster prediction and management systems His recent scholarly output reveals a strong focus on integrating cutting-edge computer vision and deep learning techniques with traditional photogrammetric methods. Analysis of his 15 most recent publications shows a clear trajectory toward more sophisticated AI-driven approaches for processing geospatial data, with particular attention to time-series analysis, uncertainty quantification, and multi-view systems. His work bridges theoretical advancements with practical applications in flood forecasting, deforestation monitoring, urban planning, and construction materials analysis. The geographic scope of his research has expanded significantly, with recent projects focusing on international case studies in the Philippines and tropical regions. Professor Heipke leads the Institute of Photogrammetry and GeoInformation, a major research hub that has celebrated 75 years of contributions to the field. His leadership extends to the Graduiertenkolleg 2159: "Integrity and Collaboration in Dynamic Sensor Networks," where he serves as a professor overseeing doctoral research. The institute maintains state-of-the-art facilities for processing satellite imagery, aerial photography, and developing novel algorithms for geospatial data analysis. Under his direction, the institute has strengthened its international collaborations and interdisciplinary research approaches, particularly in addressing Sustainable Development Goals through geospatial technologies.

Hyuck Jin ParkView profile

Professor

• Landslide Hazard Assessment
• Geotechnical Engineering
• Machine Learning Applications
• +5 more

Hyuck Jin Park is a Full Professor in the Department of Energy Resources and Geosystems Engineering at Sejong University, South Korea, where he has been teaching and conducting research since 2003. With a Ph.D. in Engineering Geology from Purdue University, his expertise spans geotechnical engineering, landslide analysis, and geospatial technologies. Professor Park has built a distinguished career in landslide hazard assessment, combining traditional geotechnical approaches with modern machine learning techniques to improve prediction accuracy and risk management. His educational background includes: B.S. in Geology from Yonsei University (1990) M.S. in Geophysics from Yonsei University (1993) Ph.D. in Engineering Geology from Purdue University (2011) Professor Park's research focuses on the spatial and temporal probability of landslide occurrence, utilizing fuzzy logic, probabilistic analysis, GIS, Monte Carlo simulation, and machine learning for landslide hazard assessment. His work integrates physically based models with statistical approaches to better understand landslide mechanisms and improve prediction capabilities. He has made significant contributions to the development of methodologies that account for geological uncertainties in hazard assessment, with applications ranging from rock slope stability to rainfall-induced shallow landslides. His recent publications demonstrate a clear trend toward integrating explainable artificial intelligence with traditional geotechnical approaches for natural hazard assessment. Professor Park's work increasingly focuses on making machine learning models transparent and interpretable while maintaining high predictive accuracy. The research spans multiple hazard types including landslides, earthquakes, and floods, with a growing emphasis on climate change impacts and data-scarce environments. With an h-index of 28 and over 3,421 citations, Professor Park has established himself as a leading researcher in his field. His work has been published in high-impact journals including Engineering Geology, Landslides, and Catena, reflecting the significance and quality of his contributions to geotechnical engineering and natural hazard assessment. Professor Park has mentored numerous researchers through collaborative projects and has secured funding for his innovative work in landslide prediction and hazard assessment. His research has involved significant international collaboration, particularly with researchers from Malaysia, Australia, and Yemen, addressing landslide and flood risks in diverse geographical contexts. He leads research activities within the Department of Geoinformation Engineering at Sejong University and has contributed to the development of specialized tools like DEWS (Distance, Elevation, Watershed, and Slope unit) for landslide early warning systems.

• Numerical Analysis
• Partial Differential Equations
• Finite Element Method
• +3 more

Dirk Praetorius is a Professor of Numerics of Partial Differential Equations (PDEs) at the Technische Universität Wien (TU Wien) , affiliated with the Institute for Analysis and Scientific Computing (ASC) within the Faculty of Mathematics and Geoinformation . He leads the research group on Numerics of PDEs and has held various leadership roles, including Institute Director (since 2020) and head of the Numerics research area. His work focuses on numerical methods for PDEs, including Finite Element Methods (FEM), Boundary Element Methods (BEM), adaptive algorithms, and computational micromagnetics. Education and Career: Praetorius earned his Diplom in Mathematics (2000) and PhD in Applied Mathematics (2003) from TU Wien, followed by a Habilitation in Numerical Analysis (2005). He has been a faculty member at TU Wien since 2005, progressing from Assistant Professor to full Professor in 2017. He has also held visiting positions at institutions such as the University of Jyväskylä and RICAM (Linz). Research Interests: His research spans numerical analysis, adaptive FEM/BEM, a-posteriori error estimation, matrix compression, and computational micromagnetics. He has contributed to modeling spin dynamics, magnetic skyrmions, and multiscale systems. His work emphasizes efficient algorithms for large-scale problems and optimal computational complexity. Awards and Editorial Roles: Praetorius received the TU Best Teacher Award (2021) and TU Best Lecture Award (2019). He serves as Senior Editor for Computational Methods in Applied Mathematics (CMAM) and on the editorial board of Applied Numerical Mathematics (APNUM) . He co-founded the outreach initiative TUForMath to promote mathematics education. Grants and Projects: He leads or co-leads several research projects funded by the Austrian Science Fund (FWF), including the collaborative SFB "Taming Complexity in Partial Differential Systems" (2017–2025) and international collaborations with Germany. His work addresses topics like functional error estimates, nonlinear PDEs, and computational design of magnetic devices. Labs and Teams: He contributes to the ASC Institute and coordinates interdisciplinary projects involving computational physics and engineering. His team develops software tools like MooAFEM and Commics for micromagnetic simulations.

Wenwen LiView profile

Professor

• Geographic Information Science
• Cyberinfrastructure
• Big Data
• +8 more

Wenwen Li is a Professor at Arizona State University (ASU), holding roles as Director of the CyberInfrastructure and Computation Intelligence (CICI) Lab and Research Director at the Spatial Analysis Research Center (SPARC). She specializes in geographic information science, cyberinfrastructure, and geospatial big data. Her work focuses on developing intelligent cyberinfrastructure for environmental and urban studies, leveraging AI and semantic technologies. Li's research has been supported by NSF, USGS, and Google.org, among others. Education: Ph.D. in Earth System and Geoinformation Science (George Mason University, 2010), M.S. in Signal and Information Processing (Chinese Academy of Sciences, 2007), and B.S. in Computer Science (Beijing Normal University, 2004). Research Interests : Cyberinfrastructure, spatial-temporal data mining, semantic interoperability, GeoAI applications in climate science, and urban studies. Her lab, CICI, pioneers projects like the Arctic Permafrost Thaw analysis and disaster response systems. Awards : 2023 AAG and UCGIS Fellowships, 2021 NSF Mid-Career Award, 2015 NSF CAREER Award, and the 2024 Greg Leptoukh Lecture Award (AGU). She chairs AAG's Cyberinfrastructure Specialty Group and serves on editorial boards of key journals. Grants & Service : Leads NSF-funded projects on GeoAI, climate modeling, and Arctic science. Active in AAG leadership roles and global initiatives like the Polar Cyberinfrastructure Portal. Recruits Ph.D. students in Geography and Computer Science. Labs & Teams : Directs the CICI Lab, advancing interdisciplinary GeoAI research and training. Collaborates with global partners on environmental and computational geography projects.

Annette EickerView profile

Professor

• Geodesy
• Satellite Gravimetry
• Gravity Field Modeling
• +4 more

Prof. Dr.-Ing. Annette Eicker is a Professor of Geodesy and Adjustment Calculations at the HafenCity University Hamburg (HCU), where she has been serving since 2016. Prior to her current position, she was an Academic Councillor at the Institute of Geodesy and Geoinformation at the University of Bonn (2014-2016), and has held visiting research positions at NASA's Jet Propulsion Laboratory in Pasadena, USA (2015) and the University of Rennes 1 in France (2014). Her research focuses on satellite gravimetry, particularly utilizing GRACE (Gravity Recovery and Climate Experiment) and GRACE-FO (Follow-On) mission data to monitor terrestrial water storage, study climate-related mass changes, and develop advanced methods for gravity field recovery. Her work bridges geodesy, hydrology, and climate science, with significant contributions to understanding global water cycle dynamics and developing next-generation gravity missions like MAGIC (Mass-change And Geosciences International Constellation). Analysis of her recent publications reveals a strong emphasis on improving the accuracy and applications of satellite gravity data for hydrological monitoring, with increasing focus on next-generation missions and daily gravity field solutions. Her research spans from fundamental method development (e.g., GROOPS software toolkit) to practical applications for water resource management and climate change monitoring. Prof. Eicker's work demonstrates leadership in the field of satellite gravimetry, with numerous publications in high-impact journals addressing critical challenges in Earth observation and climate monitoring. Though specific awards aren't mentioned in the provided materials, her extensive publication record and leadership in major projects like MAGIC indicate significant recognition within the geodetic and hydrological communities. Her research has strong implications for understanding climate change impacts on water resources, with applications in drought monitoring, flood risk assessment, and sustainable water management. She maintains active collaborations with international institutions including NASA's Jet Propulsion Laboratory and has contributed to major initiatives like the GlobalCDA Project, which integrates geodetic and remote sensing data with hydrological models.

Efstathia BuraView profile

Professor

• Dimension Reduction in Regression
• High-Dimensional Statistics
• Multivariate Analysis
• +5 more

Efstathia Bura is a Professor heading the Applied Statistics Research Unit (ASTAT) within the Institute of Statistics and Mathematical Methods in Economics at TU Wien's Faculty of Mathematics and Geoinformation. Her research focuses on dimension reduction techniques in regression and classification, high-dimensional statistics, and their applications in biostatistics, econometrics, and legal statistics. She leads projects like ProbInG (WWTF-funded) and the SecInt Doctoral College on statistical verification of cyber-physical systems. Her work integrates advanced statistical methodologies with interdisciplinary applications, emphasizing practical solutions for complex data challenges. Current projects explore probabilistic program analysis, security properties in cyber-physical systems, and dynamic econometric modeling. She collaborates internationally, with notable contributions to statistical theory and applications in law, healthcare, and telecommunications. Key research themes include time-varying regression models, sufficient dimension reduction for mixed predictors, and fusion of statistical methods with machine learning. Her publications bridge theoretical advancements and real-world problem-solving, reflecting her role as a leading academic in modern applied statistics. Her team includes postdocs and assistants working on WWTF and SecInt grants, focusing on probabilistic systems and statistical verification. While no formal student advisees are listed, her collaborative projects engage junior researchers in cutting-edge statistical research.

• Operations Research
• Public Transport Systems
• Digital Transformation
• +3 more

Leif Sörensen is a researcher at the University of Hildesheim , affiliated with the Institute of Business Administration and Business Informatics within the Faculty of Mathematics, Natural Sciences, Economics and Computer Science . His work focuses on operations research and digital transformation in public transport systems, particularly examining flexible transport models, agent-based simulations, and geoinformation system integration. Core Affiliations Researcher (since 2023) - HAWK Hochschule für Angewandte Wissenschaft und Kunst, Holzminden Doctoral Researcher - Institute of Business Administration and Business Informatics, University of Hildesheim Former Student Assistant - TU Dresden and Max Planck Institute for Self-Organization Research Focus: Sörensen's research bridges transport policy , agent-based modeling , and data analytics . He investigates how digital transformation can enhance rural mobility through flexible public transport systems , with emphasis on contractual incentives for drivers and stochastic behavior prediction . His work spans both developed and developing economies , particularly analyzing informal transit systems in South Africa. Publication Trends: Recent articles demonstrate a strong focus on operations research in transport contexts, with 7/9 publications involving agent-based simulations and DRT (Demand-Responsive Transport) . Keywords cluster around urban mobility , digital transformation , and transport resilience , while sub-fields reveal expertise in dynamic routing algorithms , passenger acceptance metrics , and GIS-integrated transport planning . Key Projects Co-author on European Commission-funded transport safety modeling Participant in Smart Hybrid research initiative (44 co-publications) Contributor to International Transportation Economics Association conferences Academic Background: Holds degrees in International Economics (University of Göttingen) and International Business and Development (University of Bayreuth). Completed internships at UNECE Geneva and KfW Entwicklungsbank Pretoria , with fieldwork in South Africa and Japan .

• Geography
• Environmental Change
• Land Cover Change
• +7 more

Tina Delahunty is an Assistant Professor in the Department of Physical and Environmental Sciences at Bloomsburg University, where she contributes to the academic and research mission in geography and environmental sciences. Her work bridges geospatial technologies with environmental change analysis. Education: Ph.D. in Geography — University of Florida M.A. in Geography — Florida Atlantic University Her research focuses on the spatial and temporal dynamics of Holocene land cover and environmental change. She employs advanced tools such as GIS, remote sensing, and palynology to investigate long-term ecological transformations. Her interdisciplinary approach integrates geospatial data with paleoenvironmental proxies to reconstruct past landscapes and assess modern environmental impacts. The recent publications highlight consistent engagement in remote sensing applications, including agricultural monitoring, urban extent mapping using nighttime lights, and ecological assessment via environmental DNA. These works reflect a strong methodological foundation in multiscale geospatial analysis and environmental monitoring across diverse ecosystems. Scientific Contributions: Co-authored research in high-impact journals such as International Journal of Remote Sensing , Freshwater Biology , and International Journal of Applied Earth Observation and Geoinformation . Active contributor to interdisciplinary environmental research involving geography, ecology, and geospatial science. She is involved in mentoring and research supervision, though specific advisees are not listed. Her work is supported by institutional affiliation and access to geospatial laboratories and field resources. She contributes to advancing methodologies in land cover classification and environmental change detection. Dr. Delahunty leads research in GIS and remote sensing laboratories at Bloomsburg, where she likely supervises student projects and collaborates on regional and global environmental studies.

Stjepan HusnjakView profile

Professor

• Soil Science
• Soil Classification
• GIS in Soil Science
• +3 more

Stjepan Husnjak is a Full Professor at the University of Zagreb's Faculty of Agriculture (Department of Soil Science), with continuous employment since 1986. He holds B.Sc. (1985), M.Sc. (1993), and Ph.D. (2000) degrees from the same institution, specializing in soil erosion, moisture regimes, and agricultural technology. His research focuses on soil science, including soil classification, GIS applications, soil genesis, degradation, and protection strategies for sustainable land use. He has led projects such as: Advanced monitoring of agroecosystems at risk of salinization/pollution (EU, 2020–2023) Biomass ash applications to enhance soil fertility (National, 2019–2020) Correlation of Croatian soils with the World Reference Base (2007–2013) His publications emphasize soil management in Croatia, erosion modeling, temperature regimes, and tillage systems, often applied to regional agricultural challenges. Administratively, he served as Head of the Department of Soil Science (2003–2011, 2015–2018) and Head of Agroecology graduate studies (2005–2017). He also held editorial roles in Agriculturae Conspectus Scientificus and Cartography and Geoinformation .

• Geographic Information Systems (GIS)
• Map Generalization
• Spatial Data Mining
• +3 more

Jan-Henrik Haunert is a Professor at the University of Bonn, affiliated with the Institute of Cartography and Geoinformatics within the Faculty of Civil Engineering and Geodetic Science. His research focuses on map generalization, geographic information systems (GIS), and optimization techniques in cartography. He has contributed to projects funded by the German Research Foundation (DFG), particularly in deriving scale-dependent representations of geographic data. His work emphasizes logical consistency, semantic accuracy, and quality assessment in geospatial data processing. Key research areas include land cover map generalization, spatial data integration (e.g., volunteered geographic information), and rule-based incremental generalization. He has developed methodologies leveraging mixed-integer programming and straight skeleton algorithms for cartographic automation. His publications span peer-reviewed journals like GeoInformatica and Photogrammetrie - Fernerkundung - Geoinformation , as well as conference proceedings such as AGILE and ACM-GIS. Haunert’s contributions address challenges in geospatial data quality, including polygon simplification and river dataset matching. He has also explored applications in vehicle localization and virtual reality systems like the GeoScope for urban planning. His work bridges theoretical GIScience with practical applications in cartography and geoinformatics.

Karolina KacprzakView profile

Researcher

• social and economic geography
• spatial management
• urban geography
• +7 more

Karolina Kacprzak is a Researcher at the Institute of Urban Geography, Tourism Studies and Geoinformation within the Faculty of Geographical Sciences at the University of Lodz . She is also a doctoral student in the Doctoral School of Social Sciences at the same university. Her research focuses on: Social and economic geography Urban planning and spatial management Overtourism and tourism traffic Impact of sharing economy platforms (e.g., Airbnb, VRBO) on urban areas Geoinformation systems Socioeconomic effects of the Covid-19 pandemic on tourism Comparative studies of Polish cities, Prague, and Barcelona Contact: karolina.kacprzak@geo.uni.lodz.pl . Office hours: Tuesday 10:00-12:00 at Kopcińskiego 31, room 204K, 90-142 Łódź.

Ana BastosView profile

Professor

• Global Carbon Cycle
• Climate Change
• Biogeochemistry
• +3 more

Ana Bastos is a Professor of Land-Atmosphere Interactions at the Institute of Earth System Science and Remote Sensing, University of Leipzig, since May 2024. She has previously held positions as a Research Group Leader at the Max Planck Institute for Biogeochemistry (2020–2024), Research Assistant at Ludwig Maximilian University of Munich (2018–2020), and PostDoc at the Laboratoire des Sciences du Climat et de l'Environnement in France (2015–2018). Her academic journey began with a PhD in Geophysics and Geoinformation Sciences from the University of Lisbon (2015) and an MSc in Energy and Environmental Engineering (2011). Her research focuses on understanding interannual to long-term variability in the global carbon cycle, integrating atmospheric science, ecology, and biogeochemistry from both observational and modeling perspectives. She investigates the links between internal climate variability and ocean-atmosphere-land teleconnections, as well as the impacts of climate extremes on ecosystem functioning and disturbance regimes. Her work often employs Earth observation data and multi-scale modeling to reconcile carbon budgets and improve climate projections. Recent publications highlight her expertise in carbon cycle dynamics, climate extremes, and ecosystem resilience. Key topics include compensatory effects in climate models, deforestation impacts on drought vulnerability, and regional greenhouse gas budget assessments. Her projects, such as ForExD and NextGenCarbon, address forest vulnerability and Earth's carbon balance under climate change. Early Career Scientist Award, Biogeosciences Division, European Geosciences Union (2022) ERC Starting Grant (2022) Elected President of EGU's Biogeosciences Division (2024) Prof. Bastos teaches courses like "Climate and Water" (BSc), "Earth System Components" (MSc), and "Earth System Modeling" (MSc). She is actively involved in initiatives promoting diversity, inclusion, work-life balance, and mental health in academia.

Martin KadaView profile

Professor

• Geoinformatics
• 3D City Modeling
• Remote Sensing
• +2 more

Martin Kada is Professor for Methods of Geoinformation Science at Technische Universität Berlin and Prodekan 'International' for Faculty VI. His research focuses on geoinformatics, 3D city modeling, and remote sensing applications. Research highlights include: Development of automated 3D building reconstruction methods Radar interferometry for deformation monitoring Machine learning for geospatial data analysis Spatial data quality assessment He has received multiple best paper awards for his work on 3D building reconstruction and geospatial data processing. Current projects involve using persistent scatterer interferometric SAR for monitoring infrastructure deformation and developing deep learning approaches for building footprint extraction.