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Ingo HeidbüchelView profile

Researcher

• Hydrology
• Catchment Hydrology
• Hydrogeology
• +3 more

Dr. Ingo Heidbüchel is a researcher in the Department of Hydrogeology at the Helmholtz Centre for Environmental Research - UFZ (Leipzig, Germany). His work focuses on understanding hydrologic processes, catchment hydrology, and transit time distributions. Previously, he held postdoctoral positions at the University of Bayreuth (2021), UFZ (2017–2020), and the GFZ in Potsdam (2013–2016). He earned his PhD from the University of Arizona (2008–2012) and a Diploma (Master equivalent) in Hydrology from Albert-Ludwigs-University Freiburg (2000–2007). Research interests include hydrologic transit times, catchment response dynamics, and hydrochemical interactions. His studies often employ tracer techniques and advanced modeling to explore processes like nitrogen cycling, groundwater-surface water mixing, and environmental change impacts on water systems. Key contributions include developing methods for analyzing transit time distributions in low-order catchments and investigating the effects of topography and seasonality on water chemistry. His work is supported by grants such as the DFG project on transit time dynamics in real-world catchments. Dr. Heidbüchel collaborates widely, contributing to initiatives like CAMELS-DE, a dataset of hydrometeorological time series for German catchments.

Mitra BaratchiView profile

Associate Professor

• Spatio-Temporal Data Analysis
• Machine Learning
• Mobility Data Modeling
• +5 more

Mitra Baratchi is an Associate Professor at the Leiden Institute of Advanced Computer Science (LIACS) , Leiden University. She leads the Spatio-temporal data Analysis and Reasoning (STAR) research group, co-leads the Automated Design of Algorithms (ADA) group, and founded the Special Interest Group on Spatio-Temporal Data Mining (SIG-SDTM) . PhD from University of Twente (Mobility Data) Master’s/Bachelor’s in Computer Engineering, Iran Research Interests focus on automated pattern extraction from spatio-temporal data across urban, environmental, and industrial domains. Key applications include: Automated Machine Learning (AutoML) for Earth Observations Time-Series Forecasting for public health (e.g., pandemic modeling) Urban Mobility Optimization with ESA, Honda, and municipalities Reliable Vehicular Communication Systems Smart Garments for Health Risk Detection Geocast Protocols for Internet-wide Communication Grant Highlights include €120K NWO-Aspasia, €2.9M Marie Skłodowska-Curie, €350K NWO-KLEIN, and €135K Center for BOLD Cities funding. She has supervised 12 PhD students and 4 current Master’s students since 2011, with notable best paper award at WWIC'16. Teaching includes Machine Learning (2020-present) and Urban Computing (2018-present) at Leiden, plus past courses in Data Visualization, Software Engineering, and Research Methods.

• Remote Sensing
• Agricultural Landscapes
• Land Use Systems
• +4 more

Christopher Conrad is a Professor of Geoecology at Martin Luther University Halle-Wittenberg, where he has served since 2019. His academic journey includes previous positions as Acting Professor at the same university (2017-2019), Junior Professor for Geographical Remote Sensing at Julius-Maximilians-University Würzburg (2011-2017), and research roles at the German Remote Sensing Data Center. He completed his habilitation on remote sensing applications for sustainable land/water use in the Aral Sea Basin in 2017 and earned his doctorate in 2006. Conrad's research integrates remote sensing, geospatial analysis, and landscape ecology to address sustainability challenges. His primary focus areas include: Agricultural landscape dynamics and land use systems Climate change impacts on water resources and migration patterns Advanced remote sensing techniques for environmental monitoring Ecosystem services assessment in vulnerable regions He leads multiple projects such as CawaGreen , MIGRAWARE , and AgriSens Demmin 4.0 focused on climate adaptation and agricultural innovation. His recent publications demonstrate strong thematic coherence around satellite-based environmental monitoring, with 63% focused on remote sensing applications, 25% on climate-water-agriculture nexus, and 12% on socio-ecological systems. The works predominantly utilize Sentinel, MODIS, and RapidEye data with machine learning integration. Conrad coordinates research teams and landscape laboratories investigating hydrological processes, soil erosion, and crop monitoring. His fieldwork spans Central Asia (Aral Sea Basin), West Africa, and European agricultural systems, emphasizing practical solutions for sustainable land management.

Thomas StetzView profile

Professor

• Smart Grids
• Energy Storage
• Photovoltaic Systems
• +3 more

Prof. Dr.-Ing. Thomas Stetz is a Professor for Electrical Power Engineering at the Technical University of Mittelhessen (Gießen, Germany), specializing in Smart Grids and Energy Storage . He is a Scientific Director of the Institute for Transformation Tasks in Energy Economics and Energy Technology (ITEE) and Project Group Leader at TransMIT GmbH, Gießen. PhD in Electrical Power Engineering (University of Kassel, 2013) Former Research Group Leader at Fraunhofer IWES (Kassel, Germany) His research focuses on technical and economic aspects of voltage control , grid integration of photovoltaics , and smart grid technologies . He has led international projects with partners like the University of Costa Rica and Ingolstadt University of Applied Sciences, funded by BMBF , BMWi , and DFG . Key article trends include reactive power optimization , automated grid planning , and storage system integration for renewable-heavy grids. His scientific awards highlight his contributions to global PV grid integration research. Best Presentation Award (CIER 2017, Havana) Science Award (German Chamber of Industry and Commerce Kassel, 2014) Prof. Stetz supervises PhD and undergraduate students and contributes to industry-standard guidelines through collaborations with Stadtwerke Gießen AG and Bayernwerk. His work bridges technical innovation and policy development for the energy transition.

Sandra Aguilar-GomezView profile

Assistant Professor

• Environmental Economics
• Gender Economics
• Health Economics
• +3 more

Sandra Aguilar-Gomez is an Assistant Professor in the Economics Department at Universidad de los Andes in Bogotá, Colombia, and will join Tecnológico de Monterrey in Mexico City in 2025. She leads the Gender Research Initiative at Environment for Development (EFD) and has held postdoctoral and visiting roles at UC San Diego. Her Ph.D. in Sustainable Development from Columbia University underpins her interdisciplinary research. Her work focuses on environmental degradation's societal impacts, particularly in low- and middle-income countries, combining environmental, gender, and health economics. Key regions include Mexico, Colombia, Cambodia, and Tanzania. Methodologically, she employs quasi-experimental designs, geospatial analysis, and satellite data. Research highlights include exploring skin tone disparities in air pollution exposure, unpaid work's gendered impacts, menstrual hygiene constraints, and climate policy. Awards include the 2020 Victor Urquidi Economic Research Award. Teaching spans environmental justice, gender economics, and development courses at multiple institutions.

Florian SteinkeView profile

Professor

• Energy Management Systems
• Machine Learning Applications in Energy
• Distributed Control Systems
• +5 more

Prof. Dr. Florian Steinke is a Professor and Head of the Energy Information Networks and Systems Department at Technische Universität Darmstadt. His academic career spans roles at Siemens Corporate Technology (2009–2016) and a PhD in machine learning at the Max Planck Institute for Intelligent Systems (2006–2008). His research focuses on algorithmic energy management, distributed control systems, machine learning applications in energy grids, and resilient smart grid design. Education: PhD in Machine Learning (Max Planck Institute for Intelligent Systems, 2006–2008) Diplom in Computational Physics (University of Tübingen & University of Washington, 1999–2005) Research Interests: Development of cyber-physical systems for energy grids Optimization of thermal-electric systems using game theory and stochastic control Integration of social media data for demand forecasting Cybersecurity measures against adversarial attacks on grids Recent work emphasizes probabilistic grid modeling, resilient energy market design, and AI-driven control strategies for Fourth Generation district heating grids. His platform ecosystem research aims to support the energy transition through data-driven solutions. Labs/Teams: Leads the Energy Information Networks and Systems research group, focusing on interdisciplinary projects combining automation, data science, and energy systems engineering.

• Public Health
• Environmental Hygiene
• Health Geography
• +7 more

Prof. Dr. med. Thomas Kistemann is a full Professor and Deputy Director at the Institute of Hygiene and Public Health, University of Bonn, and also serves as a Senior Physician (Ltd. Oberarzt) at the University Hospital Bonn. His work bridges medicine, public health, and geography, focusing on environmental health risks and urban wellbeing. His research interests include drinking water quality , Legionella and waterborne pathogens , antibiotic resistance in the environment , urban blue and green spaces and health , GIS applications in public health , and climate change impacts on health . He has published extensively on the hygienic challenges of water systems, the salutogenic effects of urban waterscapes, and socio-ecological analyses of disease outbreaks. His recent publications (2023–2025) show a strong trend toward interdisciplinary environmental health research, combining big data, spatial analysis, and microbiological monitoring. Key themes include the impact of portable air purifiers on infection control during the pandemic, GIS-based visibility analysis of green spaces, temperature dependency of Legionella, and the persistence of antibiotic-resistant bacteria in aquatic environments. His work often involves large collaborative teams and addresses both local and global health challenges. Among his scientific contributions are editorial roles and technical reports for the World Health Organization (WHO) and the European Centre for Disease Prevention and Control (ECDC), particularly on water safety and climate change impacts. He has contributed to national guidelines on drinking water hygiene and hospital infection control. Prof. Kistemann has been involved in advising and leading research groups, particularly in health geography and environmental hygiene. He has contributed to public health planning, including healthcare accessibility and bedarfsplanung (needs-based planning). His work frequently involves interdisciplinary grants and collaborative projects with institutions in Germany and internationally, including studies in Kenya, India, the Philippines, and Sweden. He is affiliated with the WHO Collaborating Centre for Water Management and Risk Communication for Health Promotion at the University of Bonn and has led research on therapeutic landscapes, urban blue spaces, and health geography education.

Ingo NeumannView profile

Professor

• Engineering Geodesy
• Geodetic Analysis Methods
• Sensor Technology
• +5 more

Prof. Dr.-Ing. Ingo Neumann is a Professor of Engineering Geodesy and Geodetic Analysis Methods at Leibniz University Hannover's Faculty of Civil Engineering and Geodetic Science. He serves as Executive Director of the Geodetic Institute and leads research in geodetic sensor systems, structural monitoring, and multi-sensor fusion. His work focuses on advancing terrestrial laser scanning (TLS), UAV-based calibration, and machine learning applications in civil infrastructure analysis. Research interests include deformation monitoring, sensor calibration, and geospatial data processing. Notable projects involve fusion of SAR/InSAR data with TLS for ground movement analysis, and development of automated damage detection algorithms for port and marine structures. He teaches courses on sensor technology, geodetic measurement methods, and industrial surveying. Publications span 2006–2025, with recent emphasis on robust outlier detection, Kalman filter applications, and B-spline modeling for structural analysis. His work integrates geodesy with computer vision and machine learning to enhance infrastructure monitoring precision.

Tino WaltherView profile

Professor

• Construction Management
• Project Control
• BIM (Building Information Modeling)
• +4 more

Prof. Dr.-Ing. Tino Walther is currently serving as Professor of Construction Management and Project Control at the Technical University of Mittelhessen (THM) since October 2023. Previously, he held roles at STRABAG AG and Bauhaus University Weimar where he completed his doctoral studies (2017-2021). His career spans academic research, industry leadership, and technical project management in civil and bridge construction. Education includes an M.Sc. in Management Studies (Construction/Real Estate/Infrastructure) from Bauhaus University Weimar (2009-2014), dual training as a civil and road construction worker with integrated studies (2007-2009), and civil engineering studies at the University of Kassel (2008-2009). Research focuses on digital transformation in construction , including BIM applications, automated data acquisition, 5D process management, and optimizing construction performance through algorithmic frameworks. His work emphasizes bridging gaps between theoretical models and practical implementation in infrastructure projects. Recent publications (2019-2024) highlight advancements in automated construction monitoring, VR-based training systems, and path-planning algorithms for heavy machinery. His methodologies integrate convex hull algorithms, point-cloud comparisons, and image recognition to improve site control and project outcomes. No scientific awards were explicitly listed in the text. His professional activities include leading construction processes departments and advising on linear infrastructure projects. He maintains active engagement with industry through collaborations like the IABSE Congress and ECPPM conferences.

Sven LautenbachView profile

Professor

• Land Use Change
• Ecosystem Services
• Environmental Modeling
• +10 more

Dr. Sven Lautenbach is a Professor and Chief Scientist at the Institute of Geoinformatics, University of Heidelberg , affiliated with the HeiGIT research group. His work bridges geospatial analysis, environmental modeling, and public health, with a focus on urban systems and land-use decision-making. Current role: Chief Scientist at HeiGIT gGmbH Key affiliations: Department of Geoinformatics, University of Heidelberg Research Interests : Lautenbach's interdisciplinary research addresses: Trade-offs in land use decisions and ecosystem services Health geography and spatial epidemiology Application of machine learning and AI to urban geospatial data Open data quality assessment (OpenStreetMap, social media) Climate adaptation strategies for urban environments Vector-borne disease risk modeling Publication Trends : Recent work emphasizes: Geo-social media for pandemic early warning systems Deep learning for infrastructure mapping (e.g., road surfaces) Flood impact analysis on urban accessibility Heat stress mitigation in pedestrian routing Multi-modal urban human dynamics during crises Open data quality evaluation for humanitarian applications Project Leadership : Lautenbach directs initiatives including: myGreen: Urban green space analysis Climate Change and Spatial Epidemiology Summer School OPERAs/FP-7: Ecosystem science-policy integration CONNECT: Biodiversity-ecosystem service synergies

Jörn OstermannView profile

Professor

• Video Coding
• Computer Vision
• Machine Learning
• +9 more

Prof. Jörn Ostermann is a Full Professor and Head of the Institut für Informationsverarbeitung at Leibniz Universität Hannover since 2003, with prior roles at AT&T Bell Labs and AT&T Labs-Research. He served as Dean of the Faculty of Electrical Engineering and Computer Science (2011–2013) and member of the Senat (since 2020). His research spans video coding, computer vision, machine learning, 3D modeling, and computer-human interfaces , with applications in SAR imaging, predictive maintenance, children's speech analysis, and cochlear implants. Key projects include Next Generation Video Coding , Conditional Coding for Learned Compression , and GreenAutoML4FAS . Notable trends in his recent publications (2025–2023) include Neural network-based video compression Uncertainty estimation in speech recognition Zero-delay coding for cochlear implants Domain adaptation for aerial image segmentation 3D mesh compression standards Error concealment in VVC coding Scientific recognitions: AT&T Standards Recognition Award (1998) ISO Award (1998) IEEE Fellow (2005) Distinguished Lecturer, IEEE CAS Society (2002/2003) MPEG Convenor (2020–2023) He co-authored a graduate textbook on Video Communications , holds >30 patents, and has led >20 research projects. His work bridges academic research and industrial standardization, particularly in MPEG and IEEE committees.

Lars BernardView profile

Professor

• (Geo-)Information Infrastructures
• Geoinformation Usability
• Distributed Geoprocessing
• +7 more

Lars Bernard is Full Professor for Geoinformatics at the Faculty of Environmental Sciences, Technische Universität Dresden since 2015. He also holds the position of Chief Digitalization and Information Management Officer (CDIO) at TU Dresden since 2020 and serves as member of the TUD Rectorate. PhD in Geoinformatics (University of Münster, 2001) Diploma in Physical Geography (University of Münster, 1995) His research focuses on (Geo-)Information Infrastructures , Distributed Geoprocessing , and Smart Environmental Monitoring . He has extensive experience in developing geospatial standards through roles in AGILE, EuroSDR, and INSPIRE initiatives. His publications demonstrate a consistent emphasis on: Metadata provision and data quality frameworks Interoperability solutions for geospatial systems Climate information service architectures User-driven provenance mechanisms As co-chair of RFII (2020-) and spokesperson for NFDI4Earth (2019-), he leads major German research data initiatives. He has advised numerous students and coordinated TU Dresden's Master Geoinformation Technologies program until 2018. Current leadership roles include serving on scientific editorial boards for Environmental Modelling & Software and International Journal of Spatial Data Infrastructures Research .

• Medical Image Processing
• Remote Sensing
• Machine Learning
• +4 more

Jianwu Dang is a faculty member at Lanzhou Jiaotong University's School of Electronic and Information Engineering , with affiliations to the Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphic and Image Processing . His academic career spans multiple institutions including a PhD from Southwest Jiaotong University in 1996. Research Interests : Focused on Medical Image Processing , Remote Sensing , and Wireless Sensor Networks , his work bridges Artificial Intelligence and Transportation Engineering , particularly in railway systems. Publications : Recent articles address Edge Computing coalition structures (2023), Extended Reality in education (2023), and Deep Learning for remote sensing (2022). Collaborations : Frequently co-authors with Yangping Wang and Zhanjun Hao , contributing to journals like IEEE Internet of Things Journal and conferences such as APSIPA .

Ilhan MutluView profile

Researcher

• Environmental Informatics
• Machine Learning
• Graph Databases
• +4 more

Dr. İlhan Mutlu is a postdoctoral researcher at the Helmholtz Centre for Environmental Research - UFZ in the Department of Computational Biology and Chemistry since 2023. Previously, he worked at TU Dresden (2021-2023) and IAV GmbH (2017-2021). He holds a PhD in Control and Automation Engineering (Istanbul Technical University, 2017) and focuses on data integration , graph databases , and machine learning models for toxicology prediction . His research bridges environmental data analysis with automated systems , particularly in freshwater toxicity assessment and optimal control techniques . Recent projects include ChEOS (toxicity prediction in European waters) and SafePol (pollinator protection). His technical expertise spans Neo4j , CleanGeoStreamR , and ecoKI platform development. Publications emphasize data curation for environmental monitoring, graph-based toxicity tools , and ML-driven chemical risk assessment . His work also involves automated driving systems , including model-free trajectory planning and robust control algorithms . Though no scientific awards are listed, his contributions span interdisciplinary domains combining environmental science with computational engineering .

• Remote Sensing
• Hydrology
• Climate Monitoring
• +5 more

Marloes Penning de Vries is an Assistant Professor at the University of Twente's Faculty of Geo-information and Remote Sensing, specializing in satellite-based environmental monitoring. Her research bridges remote sensing technology with critical Earth system processes. Her research interests focus on Remote Sensing , Hydrology , and Environmental Health , with particular expertise in satellite applications for water cycle monitoring, air quality assessment, and climate-related health impacts. Her work integrates multi-sensor satellite data to address challenges in water resources management and atmospheric composition. Analysis of her publication record reveals strong thematic continuity in satellite geophysics and environmental monitoring , with increasing emphasis on interdisciplinary applications connecting hydrology, atmospheric science, and public health. Recent work demonstrates sophisticated integration of GRACE satellite data with traditional hydrological models and expanding applications in geohealth frameworks. Her professional trajectory shows progression from atmospheric chemistry foundations to broader Earth system science applications, maintaining consistent methodological expertise in satellite data processing while expanding into water resources and health applications.