Find Academic Supervisors

Yawar HussainView profile

Researcher

• Near surface geophysics
• Geohazards
• Karst
• +5 more

Yawar Hussain is a Researcher in the Department of Sustainable Earth Systems Sciences at the University of Texas at Dallas (UTD). He holds a Visiting Professor appointment at the University of Brasília (Brazil, 2024) and has held postdoctoral fellowships at institutions including Sapienza University of Rome (Italy, 2022), University of Liège (Belgium, 2021), and Clemson University (USA, 2020). His work focuses on near-surface geophysics, geohazards, and karst systems, employing digital twin technology and multiparametric monitoring. Professional preparation includes a Junior Researcher role at the University of Brasília (2019) and postdoctoral research with Brazil's Chico Mendes Institute for Biodiversity Conservation (2018). He has earned teaching certifications from UTD’s Center for Teaching and Learning (2025) and secured grants such as the CAPESPrint mobility grant and Wallonia-Brussels International Excellence Grants. Research interests emphasize integrating seismic, electrical, and remote sensing techniques for monitoring landslides, subsurface dynamics, and anthropogenic seismicity. He pioneered a 2025 UTD seminar course using nodal seismometers to analyze infrastructure health, engaging students in hands-on data collection and analysis. His editorial work highlights Latin American geophysical applications, education, and societal impact. Awards include NSF travel grants and teaching certificates. Current projects involve multiparametric landslide monitoring, Einstein Telescope site geophysical analysis, and groundwater exploration using frequency selection methods.

• Geographic Information Systems
• Spatial Epidemiology
• Natural Disaster Management
• +5 more

Samsung Lim serves as an Associate Professor of geographic information systems (GIS) in the School of Civil and Environmental Engineering at the University of New South Wales (UNSW) Sydney. With expertise spanning data science, artificial intelligence, and machine learning, Lim applies geospatial technologies to critical real-world challenges in natural disaster management and public health research. Lim's interdisciplinary work bridges engineering, computer science, and public health domains to develop practical decision-making tools for emergency response and disease surveillance. Ph.D. in Aerospace Engineering and Engineering Mechanics, University of Texas, Austin, TX, USA M.A. in Mathematics, Seoul National University, Seoul, South Korea B.A. in Mathematics, Seoul National University, Seoul, South Korea Lim's research focuses on applying GIS to natural disaster management and public health challenges. Key areas include machine learning methods for bushfire susceptibility mapping, spatial clustering for landslide susceptibility analysis, city-scale evacuation management in flood scenarios, and social media-based natural disaster assessment. In public health, Lim investigates geo-correlations between environmental factors and asthma occurrence, computational approaches to avian influenza outbreaks, emerging hot spot analysis of COVID-19, and early detection systems for emerging infectious diseases. This work combines advanced spatial analytics with machine learning to address complex environmental and health challenges. The recent publication record demonstrates a clear interdisciplinary trajectory where geospatial science intersects with public health emergency response and natural hazard management. Lim's work consistently applies machine learning techniques to geospatial data, with particular emphasis on disaster susceptibility mapping, disease outbreak detection, and infrastructure monitoring. The research spans multiple continents and addresses both immediate emergency response needs and long-term environmental health challenges, reflecting a commitment to practical applications of geospatial science. Associate Editor of Geospatial Information Science National Delegate of Commission 3 of International Federation of Surveyors (FIG) National Representative of the International Cartographic Association (ICA) Commission on Sensor-driven Mapping Senior Member of Institute of Electrical and Electronics Engineers (IEEE) Lim actively contributes to the development of early warning systems for emerging infectious diseases through collaborations with public health researchers. The work on EPIWATCH demonstrates how AI can enhance surveillance capabilities for outbreak detection. Lim's research on cruise ship transmission of diseases and the spread of avian influenza through bird migration patterns and poultry trade networks shows strong engagement with real-world public health challenges. These projects often involve multidisciplinary teams spanning engineering, computer science, epidemiology, and veterinary medicine. Lim's work integrates multiple geospatial data sources and analytical techniques to address complex environmental and public health challenges. This includes developing frameworks for performance analysis of OpenStreetMap data, creating specialized road datasets for pedestrian navigation, and applying Persistent Scatterer Interferometry for land motion monitoring. The research combines traditional geospatial methods with cutting-edge machine learning approaches to extract meaningful insights from complex spatial datasets.

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.

Fabio TostiView profile

Professor

• Ground Penetrating Radar (GPR)
• Non-Destructive Testing (NDT)
• Civil Infrastructure Monitoring
• +7 more

Professor Fabio Tosti is a Professor of Civil Engineering and Director of the Faringdon Research Centre at the University of West London , School of Computing and Engineering. He holds a PhD and MSc from Roma Tre University, Italy, and has been a key figure in advancing Ground Penetrating Radar (GPR) and non-destructive testing (NDT) in civil and environmental engineering. PhD in Civil Engineering, Roma Tre University (2014) MSc in Road Transportation and Infrastructures, Roma Tre University (2010) His research centers on non-destructive evaluation of civil infrastructure using GPR, microwave tomography, and remote sensing (e.g., InSAR). He has led projects within the COST Action TU1208 and co-convener of GPR sessions at the EGU General Assembly . He teaches across BEng, MEng, and MSc programs in civil and environmental engineering. The articles listed span from 2020 to 2025, showcasing a consistent focus on infrastructure and environmental monitoring. Key research trends include bridge and runway deformation monitoring using satellite radar (InSAR), tree root and trunk assessment via GPR, data fusion of multi-sensor systems, and advanced signal processing techniques like reverse-time migration and joint inversion. His work bridges geophysics, civil engineering, and environmental science, with applications in transportation, urban forestry, and heritage conservation. Notable scientific recognition includes the GI Division Outstanding ECS Award Lecture at EGU 2017. Prof. Tosti actively supervises research, collaborates internationally, and contributes to editorial boards, including as Assistant to Editors for Advances in Transportation Studies . He has led and participated in numerous European and Italian research projects, demonstrating sustained funding and leadership. His work often involves interdisciplinary teams, including researchers from Italy, the UK, and the Netherlands. He is a recognized expert in transport infrastructure health monitoring , with a strong emphasis on smart, non-invasive methods for roads, railways, bridges, and airport runways. His lab and research group focus on developing integrated sensing systems combining GPR, InSAR, LiDAR, and machine learning for real-world engineering challenges.

• Computer Vision
• Pattern Recognition
• Machine Learning
• +7 more

Prof. Dr.-Ing. Joachim Denzler is a Professor leading the Chair for Digital Image Processing (Lehrstuhl für Digitale Bildverarbeitung) at Friedrich-Schiller-Universität Jena. His research spans computer vision, machine learning, medical imaging, and remote sensing applications across diverse domains including biomedical analysis, environmental monitoring, and facial recognition systems. His research interests focus on explainable AI, causal discovery, physics-informed neural networks, and bias mitigation in deep learning models. He has made significant contributions to fine-grained classification, concept activation vectors, and privacy-preserving techniques in facial recognition. His work often bridges theoretical computer vision with practical applications in medical diagnostics, environmental science, and infrastructure monitoring. His recent publications demonstrate a strong trend toward causal discovery methods, physics-informed neural networks, and addressing bias in machine learning systems. His work spans both theoretical advancements in model interpretability and practical applications in medical imaging, environmental monitoring, and infrastructure safety. The interdisciplinary nature of his research is evident from collaborations with ecologists, neuroscientists, and civil engineers. Best Paper Award at International Conference on Pattern Recognition (ICPR) 2024 Prof. Denzler actively mentors numerous PhD students and postdoctoral researchers, with frequent co-authors including Maha Shadaydeh, Niklas Penzel, Gideon Stein, and Tim Büchner appearing as first authors on significant publications. His laboratory has secured research funding across multiple domains including medical imaging, environmental monitoring, and AI safety. His work on CausalRivers represents a major contribution to benchmarking causal discovery methods with real-world time series data. The Chair for Digital Image Processing maintains strong industry and clinical partnerships, particularly in medical imaging applications for facial palsy analysis and neonatal care. Prof. Denzler's team has developed novel techniques for dam deformation monitoring using remote sensing data and created advanced methods for analyzing plant diversity effects on ecosystem functioning.

• Geophysics
• Remote Sensing
• Interferometric Synthetic Aperture Radar (InSAR)
• +7 more

Dr. Zhong Lu is the Shuler-Foscue Professor of Earth Sciences at Southern Methodist University (SMU) , where he has served since 2013. He is a leading expert in geophysics and remote sensing, with a focus on InSAR (Interferometric Synthetic Aperture Radar) applications for monitoring geohazards such as landslides , volcano deformation , land subsidence , and human-induced geohazards . Education: Ph.D. in Geophysics, University of Alaska Fairbanks (1996) M.S. in Geophysics, Peking University (1992) B.S. in Geophysics, Peking University (1989) Research Focus: Dr. Lu's research integrates remote sensing , geodetic modeling , and machine learning to study surface deformation and geohazard mechanisms. His work spans from Alaskan volcanoes to Texas sinkholes , and from coastal subsidence to glacial landslides . Key Projects: He has led or co-led numerous NASA and USGS funded projects, including mapping land deformation over the Gulf Coast , monitoring Aleutian volcanoes , and developing InSAR-based landslide inventories for the Pacific Northwest. Awards & Honors: Elected Fellow of the American Association for the Advancement of Science (AAAS) Featured in NASA/ASF 25th Anniversary Brochure Multiple journal covers and media recognitions Teaching & Mentorship: Dr. Lu teaches courses such as Radar Interferometry , Remote Sensing Principles , and Geodynamics , and is actively recruiting Ph.D. students with interests in geohazard monitoring and modeling. Labs & Teams: He leads a research group at SMU focused on advanced InSAR techniques and collaborates with USGS, NASA, and international institutions on satellite-based geohazard monitoring.

John Peter Merryman BoncoriView profile

Professor

• Remote Sensing
• Synthetic Aperture Radar (SAR)
• Glaciology
• +4 more

John Peter Merryman Boncori serves as Head of Microwaves and Remote Sensing at the Department of Space Research and Technology, Technical University of Denmark (DTU). His research directly contributes to UN Sustainable Development Goals through advanced Earth observation techniques. His research spans Remote Sensing , Synthetic Aperture Radar , and Glaciology , with specific expertise in InSAR processing for tectonic monitoring and ice sheet dynamics. Key focus areas include: Greenland Ice Sheet velocity measurement using SAR Multi-scale analysis of active fault systems in Italy Validation of ground motion services using GNSS Subglacial hydrology modeling in polar regions Dr. Boncori actively supervises PhD research in critical areas: Crowd counting via remote sensing (CroCo project) Field-scale soil moisture mapping InSAR error characterization Ship tracking with iceberg discrimination Ice velocity retrieval using TOPS-mode SAR He leads the Microwaves and Remote Sensing group at DTU Space, developing advanced methodologies for radar interferometry and satellite-based deformation monitoring. His team maintains strong international collaborations across Europe for Earth observation projects, with particular emphasis on cryosphere and tectonic applications.

Bénédicte FruneauView profile

Associate Professor

• Radar Interferometry
• Geophysics
• Remote Sensing
• +4 more

Bénédicte Fruneau is an Associate Professor at Université Gustave Eiffel and a member of the ACTE research team within LASTIG (Laboratory of Studies and Research in Geomatics). She serves as co-coordinator of the Master 2 Geographical Information, Spatial Analysis and Remote Sensing program. Her expertise lies in radar interferometry for ground deformation monitoring and seismic cycle studies. Research Interests : DInSAR and MTInSAR techniques Seismic cycle deformation analysis Urban and suburban displacement monitoring Residual mining subsidence characterization Publications focus on satellite radar interferometry applications for glacier monitoring , forest phenology , anthropogenic deformation , and post-mining subsidence . Her work spans geophysics, remote sensing, and geotechnical risk assessment across France, Taiwan, Mexico, and India. Education : Habilitation (HDR) in Radar Interferometry, Université Paris-Est (2011) PhD in Geophysics, Université Paris 7 (1995) MSc in Signal/Image/Parole, Grenoble INP (1991) Electrical Engineering degree, Grenoble INP (1991)

• Interferometric radar remote sensing
• Geophysics
• Planetary science
• +5 more

Howard Zebker is the Kwoh Ting Li Professor in the School of Engineering and Professor of Geophysics at Stanford University. He specializes in interferometric radar remote sensing, with applications in Earth and planetary studies. His research includes radar interferometry, geodesy, and planetary surface analysis, particularly through NASA missions like Cassini to Saturn's moon Titan. Roles: Department Chair (Geophysics, 2013–2019), Associate Chair (Electrical Engineering), NASA advisory roles Education: PhD (Stanford, 1984), MS (UCLA, 1979), BS (Caltech, 1976) Research focuses on radar technologies for terrain mapping, subsurface processes, and environmental monitoring. Notable contributions include radar interferometry for mm-scale deformation measurements and studies of volcanic and permafrost dynamics. Publications (highlighted trends): Recent work emphasizes Arctic permafrost monitoring, soil moisture retrieval via InSAR, and Venus exploration through the VERITAS mission. Earlier contributions include Cassini radar analysis of Titan's surface and deformation studies using InSAR. Awards: AGU/IEEE Fellowships, Dana Adams Griffin Award, multiple NASA Certificates of Achievement Grants: Led NSF EarthScope projects and participated in NASA mission science teams Labs/Teams: Active in WInSAR consortium, Stanford's radar remote sensing group, and planetary science collaborations.

Christiane SchmulliusView profile

Professor

• Earth Observation
• Remote SensING
• Climate Change Monitoring
• +3 more

Christiane Schmullius is a Professor at the Department for Earth Observation within the Faculty of Chemistry and Earth Sciences at Friedrich Schiller University Jena. Her research focuses on Earth observation using optical, thermal, and microwave (radar) sensors for geoscientific applications, particularly climate change monitoring and biomass mapping. She has led major projects like the ALOS Kyoto & Carbon Initiative and Global Forest Observations Initiative (GFOI) , and contributed to international collaborations such as the Climate Change Initiative (CCI) Forest . Education: PhD in Earth Sciences from Free University of Berlin (1991), MA in Remote Sensing from UC Santa Barbara (1986). Key Research Areas: Satellite radar for land cover analysis, climate change mitigation, big data handling from Sentinel satellites, and savanna/forest ecosystem monitoring in Africa and Siberia. Her recent publications analyze land cover seasonality, woody cover dynamics in savannas, and SAR data fusion for biomass estimation. She has supervised over 130 theses, including 50+ PhDs, and received accolades like the German Federal Cross of Merit (2010) and leadership roles in the International Astronautical Congress .

Stefan HinzView profile

Professor

• Remote Sensing
• Photogrammetry
• InSAR
• +5 more

Prof. Dr.-Ing. Stefan Hinz is a Professor at the Karlsruhe Institute of Technology (KIT), serving as Spokesperson for the Topic Data Science in Climate and Environmental Research within the KIT Climate and Environment Center. He is based at the Institute for Photogrammetry and Remote Sensing (IPF) in Karlsruhe, Germany, where his work bridges advanced remote sensing methodologies with critical environmental and climate challenges. His research spans Remote Sensing , Photogrammetry , and Environmental Monitoring , with specialized expertise in InSAR, GNSS, and deep learning applications. Key focus areas include land subsidence analysis (particularly in the Mekong Delta), infrastructure safety monitoring for dams and bridges, atmospheric dust density estimation, and climate adaptation strategies through spatial planning. His interdisciplinary approach integrates geospatial data science with practical environmental solutions. Recent publications reveal a pronounced shift toward AI-driven remote sensing, with deep learning techniques enhancing traditional methods like SAR interferometry. His work emphasizes real-world applications in geohazard monitoring, environmental protection, and climate resilience, often targeting vulnerable regions like the Mekong Delta. This trend reflects a broader movement toward computational innovation in earth observation science. Prof. Hinz leads strategic initiatives within the KIT Climate and Environment Center, coordinating data science efforts for climate research and environmental protection. His role involves fostering cross-disciplinary collaboration to address sustainability challenges through advanced remote sensing technologies and spatial data analysis.

• Remote Sensing
• Earth Observation
• Radar Interferometry
• +7 more

Professor Linlin Ge is a distinguished academic specializing in remote sensing and earth observation at the University of New South Wales (UNSW), Sydney, Australia. He holds a position in the School of Civil and Environmental Engineering and has been studying earth observation techniques since 1985. His work has significant applications in natural disaster monitoring, land subsidence measurement, and integrating radar and optical remote sensing with GPS and GIS systems. Professor Ge's educational background includes a PhD in GPS and remote sensing from UNSW, an MSc in Crustal Deformation from the Institute of Seismology, and a BEng (1st Hons and University Medal) in Optical Engineering from the Wuhan Technical University of Surveying and Mapping. He was also a postdoctoral research fellow in the Meteorological Research Institute of the Japan Meteorological Agency sponsored by the Science and Technology Agency of Japan during 1997-1998. His research interests focus on using digital images to map the Earth's surface, combining remote sensing with GPS and GIS to produce cost-effective and reliable maps, and integrating radar and optical remote sensing with GPS and GIS to measure subtle surface changes with minimal latency. Professor Ge's work aims to make remote sensing more timely, accurate, affordable, and widely applicable across various disciplines. His recent publications demonstrate a strong focus on advanced remote sensing techniques, particularly in the areas of hyperspectral image classification, landslide monitoring, earthquake damage assessment, and land subsidence analysis. His research increasingly incorporates deep learning and AI approaches while maintaining strong applications in natural disaster monitoring and management. Major Awards: JK Barrie Award for Overall Excellence (2008 Asia-Pacific Spatial Excellence Awards) NSW Scientist of the Year 2009 (Physics, Earth Sciences, Chemistry and Astronomy) UNSW Inventor of the Year finalist (2010) Australian Research Council Postdoctoral Fellowship (2002-2004) Professor Ge has supervised 25 graduated students and currently has 5 students in his lab. His research is supported by multiple grants including ARC Discovery grants, Australian Space Research Program funding, and various government and industry partnerships focused on SAR formation flying, subsidence monitoring, flood mapping, and carbon capture safeguarding. His work with satellite missions such as Envisat, ALOS, COSMO-SkyMed, Radarsat-2 and ALOS-2 demonstrates his leadership in practical applications of remote sensing technology.

• Synthetic Aperture Radar (SAR)
• Remote Sensing Technology
• Geomatic Engineering
• +4 more

Othmar Frey is a Senior Scientist and Lecturer at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering. He leads the research group on SAR Remote Sensing Technology and is associated with the Chair of Earth Observation and Remote Sensing. His work focuses on developing advanced radar systems and applications, including car-borne and UAV-based SAR for deformation monitoring, multi-static SAR constellations, and tomographic profiling of snow and forest structures. Frey holds a Ph.D. (2010) and M.Sc. (2002) from ETH Zurich and the University of Zurich. Education: Ph.D. (Hons.) in Science (2010) from the University of Zurich, Switzerland; M.Sc. (Hons.) in Geomatic Engineering (2002) from ETH Zurich. Research interests span Synthetic Aperture Radar (SAR) signal processing, interferometry, tomography, and remote sensing applications for environmental and civil engineering challenges. Notable projects include railway substructure monitoring via TerraSAR-X data, development of compact SAR systems (GLSAR/GSSAR), and the Alpine Measurement Lab for studying mass movements. His team collaborates with agencies like ESA, Innosuisse, and the Swiss Federal Office for the Environment. Advising: Supervises PhD students like Magnus Heimpel and Fanyun Xu, with former advisees now at EMPA, Leica Geosystems, and ITU. Research teams include the Earth Observation and Remote Sensing group at ETH Zurich.

Ann ChenView profile

Associate Professor

• SAR/InSAR Algorithm Design
• Earth System Science
• Natural and Induced Seismicity
• +3 more

Ann Chen is an Associate Professor in the Department of Aerospace Engineering and Engineering Mechanics at The University of Texas at Austin, with a courtesy appointment in the Department of Geological Sciences. She leads the Radar Interferometry Group at the Center for Space Research, focusing on advancing InSAR techniques for earth system science applications. Her research addresses critical issues such as natural and induced seismicity, groundwater resource monitoring, natural disaster assessment, and permafrost hydrology and carbon storage dynamics. Her work integrates satellite-based remote sensing with geophysical modeling to study subsurface deformation patterns linked to human activities (e.g., fluid injection) and environmental processes. Collaborations span academic and industrial sectors, emphasizing scalable InSAR solutions for large-scale basins like the Permian Basin and Delaware Basin. Her affiliations include dual roles at the Cockrell School of Engineering and Jackson School of Geosciences, fostering interdisciplinary research. Ann has developed innovative methods for InSAR data processing, including interferogram subset analysis and GNSS calibration strategies to enhance monitoring in challenging environments. Her contributions have advanced applications in coastal subsidence risk assessment, Arctic permafrost dynamics, and aquifer system characterization. Her teaching includes graduate-level courses in geophysical imaging systems, computational methods, and numerical methods in geosciences. She actively mentors researchers in radar interferometry, geohazard monitoring, and environmental geophysics.

Hamza AlkhatibView profile

Researcher

• Bayesian Modelling
• Monte Carlo Methods
• Uncertainty Modelling
• +5 more

Hamza Alkhatib is a Senior Researcher at the Geodetic Institute within the Faculty of Civil Engineering and Geodetic Science at Leibniz University Hannover. His research focuses on advanced computational methods in geodetic data analysis, including Bayesian modeling, Monte Carlo simulations, uncertainty quantification, and filtering techniques for multi-sensor systems. He leads projects funded by DFG, BfG, and BMVI, addressing topics like hydrographic monitoring, cooperative sensor networks, and machine learning applications in geodesy. Alkhatib holds a PhD from the University of Bonn (2007) and a Habilitation from Leibniz University Hannover (2020). Education & Career : PhD (2007): University of Bonn, Dissertation on Monte Carlo methods for satellite gravity missions Habilitation (2020): Leibniz University Hannover, Advanced methods in geodetic data analysis Senior Research Staff since 2019 Research Interests : Bayesian inference and robust statistical methods Filtering algorithms (Kalman, Particle Filters) for dynamic systems Machine learning for geodetic point cloud analysis and damage detection Sensor fusion and multi-sensor positioning systems Hydrographic monitoring and marine infrastructure assessment Key Projects : DFG-funded adaptive robust adjustment of geodetic measurement processes Research Training Group GRK 2159 on dynamic sensor networks WaMUT project for hydrographic water change zone monitoring 3D HydroMapper for port infrastructure inspection Awards : DAAD Award for Outstanding Achievements (2000) Syrian Ministry of Academic Education Award (1998) Teaching : Teaches courses on geodetic data analysis, recursive state estimation, and machine learning applications at both bachelor and master levels.