Prof. Dr. Thomas Brinkhoff is Chair of the Institute Board and Chair of Geoinformatics at Oldenburg University of Applied Sciences. He leads the Institute for Applied Photogrammetry and Geoinformatics (IAPG) and contributes to institutions like the Association for the Promotion of Geoinformatics in Northern Germany (GiN e.V.) and the Oldenburg Research and Development Institute for Computer Science (OFFIS e.V.). Education: Diploma in Computer Science (Informatik), Universität Bremen (1990) Doctorate in Computer Science (Dr. rer. nat.), Ludwig Maximilian University of Munich (1994) Brinkhoff's research spans geodatabase systems, spatiotemporal data processing, geosensor analytics, and location-based services. His work addresses Volunteered Geographic Information (VGI), web-based geospatial visualization, and mobile data integration, with applications in traffic management and forensic science. Recent projects include ProSaDi (Digital Provenance and Collection Research) and contributions to the Laboratory for optical 3D metrology . He has served on program committees for ACM SIGSPATIAL (2002-2019), AGILE conferences (2010-2025), and editorial boards of journals like GeoInformatica and TGIS. Notable Lectures: 2024: Forensic applications of tachograph data 2023: Geoinformatics in homicide investigations 2022: Spatiotemporal analysis for sustainability projects 2015: Open geodata standards at FOSSGIS 2014: Mobile sensor data processing
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.
Axel Dreher is Professor of International and Development Politics at Heidelberg University’s Alfred-Weber-Institute for Economics. He is a leading scholar in political economy and development economics, with extensive affiliations including the German National Academy of Sciences Leopoldina, CEPR, CESifo, KOF, AidData, and EUDN. He serves as Editor of the Review of International Organizations and Co-Director of the Center for European Studies (CefES) at the University of Milan-Bicocca. Ruprecht-Karls-University Heidelberg (2011–Present) Georg-August University Göttingen (2008–2011) ETH Zurich (2005–2008) University of Konstanz (2004–2005) University of Exeter (2003–2004) University of Mannheim (2000–2003) His research centers on political economy , economic development , foreign aid , and globalization . He investigates how political institutions, leadership incentives, and geopolitical interests shape development outcomes and international financial flows. His work often employs empirical and geospatial methods to analyze aid allocation, corruption, migration, and the rise of emerging donors like China. The 15 most recent publications reflect a strong focus on China’s overseas development finance , regional favoritism , and the political determinants of aid . Keywords span political economy, development economics, and international relations, with subfields including Chinese foreign aid, geospatial analysis, governance, institutional quality, and South-South cooperation. His recent book Banking on Beijing and award-winning paper Wedded to Prosperity exemplify his cutting-edge contributions to understanding the political economy of development. Scientific awards include: 2023 Best Paper Award, Political Economy of Aid Society (PEAS) 2023 Best New Dataset Award, International Political Economy Society International Geneva (IG) Award 2020 Excellence in Refereeing Award, World Bank Economic Review (2019) 2010 KfW Excellence Award for policy-relevant research Multiple DFG and Swiss research grants Dreher has advised over 30 PhD students on topics ranging from aid effectiveness to political violence and migration. He has received major research grants from the German Research Foundation (DFG), Swiss Network for International Studies (SNIS), European Commission, and VolkswagenStiftung. His leadership roles include organizing the annual Political Economy of International Organizations conference series and serving on editorial boards of top journals such as World Development and Defence and Peace Economics . He is actively involved in academic labs and research networks including the Courant Research Center on Poverty and Equity at Göttingen, AidData at William & Mary, and the Center for European Studies (CefES). His current work continues to explore the intersection of politics, development, and globalization, particularly through georeferenced data and natural experiments.
Dr. Jing Wang is a Professor in the Department of Bioinformatics at Southern Medical University's School of Medicine, with extensive research at the intersection of artificial intelligence and biomedical applications. Her work demonstrates strong cross-disciplinary collaboration across medical institutions, engineering departments, and computer science research groups. Her primary research interests include Artificial Intelligence in Healthcare , Biomedical Engineering , and Traditional Chinese Medicine Informatics , with recent publications showing particular expertise in medical imaging analysis, diagnostic assistance systems, and clinical decision support. Her work spans both theoretical algorithm development and practical clinical implementations. Analysis of her 15 most recent publications (2025-2026) reveals a strong trend toward clinically applicable AI systems, with approximately 60% of publications focused on medical diagnostics and treatment support systems. The remaining publications demonstrate expertise in industrial applications of computer vision and fundamental AI research. Her work shows consistent collaboration with both domestic Chinese institutions and international research groups. Notable scientific contributions include: Development of 'Tianyi', a traditional Chinese medicine language model for clinical practice Innovations in bionic soft robotics for rehabilitation assistance Novel approaches to medical image analysis for cancer diagnostics Her research program appears well-funded with consistent publication output across high-impact journals in biomedical engineering, AI, and medical informatics. Current work suggests strong emphasis on translating AI research into clinical practice, particularly in diagnostic support systems and rehabilitation technology.
Hao Liu is a researcher affiliated with institutions like Chinese Academy of Sciences , Beihang University , and Stanford University . His work spans Computer Science , Artificial Intelligence , and Robotics . Key affiliations: National Space Science Center (Beijing), School of Astronautics (Beihang), Key Laboratory of Pervasive Computing (Tsinghua) Research interests include Machine Learning , Image Processing , Graph Neural Networks , and Wireless Communication Optimization His recent publications focus on: Advanced control systems for fuzzy models Medical imaging via hyperspectral analysis Transformer-based approaches in NLP and vision Quantum-safe and edge computing protocols
Philipp Otto is a Professor of Statistics and Data Science at the University of Glasgow. Previously, he was a Reader in Statistics and Data Analytics (2023–2024) and held a Junior Professorship in Big Geospatial Data at Leibniz University Hannover (2018–2023). He earned his PhD in Statistics (summa cum laude) from European University Viadrina in 2016 and a B.Sc. in International Economics, with study visits to Saint Petersburg State University. His research focuses on spatial and spatiotemporal statistics, environmetrics, network modeling, and machine learning applications. Education: PhD in Statistics (2016), European University Viadrina, Frankfurt (Oder) B.Sc. in International Economics (with study visits to Saint Petersburg) Research Interests: Philipp’s work centers on spatial statistics, spatiotemporal volatility modeling, environmental data analysis, and network processes. He develops statistical methods for geo-referenced and network data, with applications in climatology, finance, and environmental risk assessment. His contributions include advancements in GARCH models, spatiotemporal clustering detection, and statistical process monitoring for AI systems. Grants & Projects: He has secured €1,038,847 in research grants, leading projects on historical map time series analysis, agricultural air quality impacts, and high-dimensional spatial dependence structures. Industry collaborations include survival analysis for building information models. Awards: 2017 Fellowship to attend the Lindau Nobel Laureate Meeting (Economic Sciences) 2017 Best Presentation Award (Data Science, Statistics, and Visualisation) Teaching: He teaches statistics and data science across disciplines, including economics, engineering, and mathematics, at both undergraduate and postgraduate levels. Professional Activities: Editorial Boards: Environmetrics (2021), AStA Advances in Statistical Analysis (2020) Member of German Statistical Society (Treasurer, 2013)
Ahmed Elbeltagi is an Assistant Professor in the Agricultural Engineering Department at Mansoura University's Faculty of Agriculture. His work focuses on hydrology, agricultural water management, and climate change adaptation. Specializes in data-driven modeling for water resource optimization Integrates machine learning with traditional hydrological models Active in climate change impact assessments on agricultural systems Recent research trends include: Developing open-source tools like Aqua-MC for irrigation simulation Applying hybrid deep learning models for evaporation prediction Advancing water quality assessment through multivariate analysis Exploring economic applications of wetlands in arid regions He collaborates with institutions across Egypt, India, China, and Saudi Arabia, with a focus on sustainable water management solutions.
Dr. Gaël Kermarrec is a researcher at the Boundary Layer Meteorology Group , part of the Institute of Meteorology and Climatology within the Faculty of Mathematics and Physics at Leibniz University Hannover . His work focuses on atmospheric turbulence, GNSS applications, and remote sensing for environmental monitoring. Boundary layer meteorology Turbulence theory GNSS signal processing Terrestrial laser scanning Climate change impacts Geodetic time series analysis His research integrates advanced mathematical models like LR B-splines and Matérn covariance with large eddy simulations to study: Atmospheric turbulence effects on optical/GNSS signals Hydrospheric mass loading Deformation analysis of terrain/port infrastructure Climatic sea-level changes Machine learning for remote sensing The 15 most recent articles (2025-2023) demonstrate his focus on: GNSS-based turbulence detection AI-enhanced climate mapping Advanced surface approximation techniques Multi-sensor data fusion Stochastic modeling of geodetic observations Environmental impacts on optical measurements He has developed tools like the Klimascanner QGIS plugin for urban climate resilience and contributes to: Understanding atmospheric scale lengths Improving TLS/GNSS deformation monitoring Analyzing hydrospheric changes Wavefront modeling Ionospheric corrections
Prof. Dr. med. Andreas Stahl is a faculty member at the University of Greifswald , serving as the Director of the University Eye Clinic . His work integrates clinical practice and research in ophthalmology, with a focus on retinal diseases. University: University of Greifswald Role: Director of the Clinic Contact: clinic-management-eyes@med.uni-greifswald.de Research Interests: Stahl’s research centers on retinopathy of prematurity (ROP) , anti-VEGF therapies , angiogenesis , and diabetic retinopathy . He explores pathophysiological mechanisms and innovative treatments for retinal vascular disorders, collaborating across disciplines to improve neonatal and adult ophthalmological outcomes. Recent Publications: His 2021–2022 work includes clinical decision support tools for ROP screening, comparative studies of ranibizumab and laser therapy, and analyses of retinal vascular occlusion post-COVID vaccination. These reflect his commitment to advancing treatment protocols and understanding disease mechanisms. Teaching: Involved in student education and e-learning development for ophthalmology. Projects: Participates in the INTERREG European Region Pomerania (INT118) initiative.
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
Dr. Yelda Turkan is an Associate Professor in the School of Civil and Construction Engineering at Oregon State University and a Hans Fischer Fellow at the Technical University of Munich (TUM-IAS). Her research focuses on leveraging computer vision, machine learning, and digital twins to enhance sustainability and resilience in the built environment. She holds a Ph.D. in Civil Engineering from the University of Waterloo, Canada, and dual B.Sc. degrees in Civil Engineering and Geomatics Engineering from Istanbul Technical University, alongside an M.Sc. in Remote Sensing. Her work integrates advanced technologies like LiDAR and BIM to improve construction monitoring, structural safety, and fire protection. She has authored over 80 peer-reviewed publications and secured $4.5M in grants from agencies like the NSF. Dr. Turkan serves as Vice President of the International Association for Automation and Robotics in Construction and chairs the ASCE Computing Division Executive Committee. Her research spans digital twins for infrastructure performance, fire safety simulations, and automated progress tracking. Key contributions include frameworks for bridge construction monitoring, fire safety management in timber structures, and BIM-based energy fault detection. Awards include the Robert C. Wilson Faculty Scholar (2023–2025) and ASCE ExCEEd Teaching Fellow (2015).
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.
Ana Lucic is an Assistant Professor in Artificial Intelligence at the University of Amsterdam , with a joint appointment between the Institute for Logic, Language and Computation and the Informatics Institute . Her research focuses on interpretable machine learning applications for scientific discovery and societal impact. Formerly at Microsoft Research AI for Science and Partnership on AI PhD in Explainable Machine Learning from University of Amsterdam (2022) BSc/MSc in Mathematics from McMaster University Research Highlights: Develops mechanistic interpretability methods for deep learning architectures. Created Aurora , a foundation model for Earth system forecasting outperforming traditional operational models in air quality prediction and tropical cyclone tracking. Pioneers Clifford-Steerable CNNs for geophysical data analysis. Actively hiring PhD students for AI transparency research . Collaborative Networks: Contributions to ELLIS Summer School and ICML workshops . Collaborates with Microsoft Research AI for Science team on climate-related ML projects. Involved in organizing TerraBytes workshop at ICML 2025. Recent Advancements: Key role in publishing Aurora model in Nature (2025), demonstrating superior performance in Earth system forecasting. Supervises Ege Erdogan , new PhD student focused on mechanistic interpretability. Actively contributes to open-source AI development through GitHub repositories and technical discussions.
Prof. Felix Bießmann holds a professorship in Computer Science and Media at Berlin University of Applied Sciences' Department VI. His research focuses on machine learning applications in diverse fields including healthcare, urban planning, environmental science, and robotics through his Cognitive Algorithms Lab. He teaches courses such as Machine Learning, Deep Learning, and Data Science Workflows, alongside roles at TU Berlin and Korea University. Education: PhD (Dr. rer. nat.) in Natural Sciences Research interests span machine learning theory and practical implementations across domains like computer vision, generative AI, and sensor data analysis. His work addresses challenges in automated systems, healthcare monitoring, and sustainable technologies. Recent student theses explore topics like license plate recognition, adaptive game soundtracks, and bird song detection using TinyML. Collaborations include projects with the Charité Berlin and Robert-Koch Institute. Lab: Cognitive Algorithms Lab (developing machine learning methods/applications) Contact: felix.biessmann@bht-berlin.de | Office D138, Berlin University of Applied Sciences.
Clemens Kroneberg is a Professor of Sociology at the Institute of Sociology and Social Psychology, University of Cologne. His research spans diversity and boundary making, action theory, social networks, and crime and deviance, with a focus on integrative theoretical frameworks like the Model of Frame Selection. He leads major projects including the ERC Starting Grant project SOCIALBOND and the DFG project Friendship and Violence in Adolescence , analyzing longitudinal data on social networks, identities, and juvenile delinquency. Principal investigator at University of Cologne Guest Professor at McGill University (2022-2024) His research integrates cognitive social psychology with rational choice theory, applying the Model of Frame Selection to altruism, crime, political participation, and trust. Recent work examines post-pandemic juvenile delinquency trends, ethnic diversity in schools, and institutional trust in public goods provision. Key scientific accolades include the Robert K. Merton Best Paper Award (2021) and Fellow of the European Academy of Sociology . He advises PhD students in areas related to social network analysis, panel analysis, and criminological theories. Advises students on diversity policies and racism Collaborates with institutions like ECONtribute Center of Excellence, Mannheim Centre for European Social Research
