جست‌وجوی استاد و پژوهشگر

Sebastian van der Lindenمشاهده پروفایل

استاد

• Remote Sensing
• Geoinformation Science
• Land Use and Land Cover Change
• +۳ مورد دیگر

Sebastian van der Linden has been a Professor of Geography at the University of Greifswald since 2019, heading the Earth Observation and Geoinformation Science Lab within the Institute of Geography and Geology. His institutional roles include: Member of the Greifswald Moor Center (GMC) since 2020 Member of the EnMAP Science Advisory Group (EnSAG) since 2021 Deputy Director of the Interdisciplinary Research Centre on Baltic Sea Region Research (IFZO) since 2022 His research centers on Earth observation methodologies using multi- and hyperspectral remote sensing data to analyze spatiotemporal dynamics of land use, land cover, and environmental processes. Specialized expertise includes peatland monitoring (particularly rewetting impacts), climate change effects on vegetation systems, and machine learning-driven land cover mapping at local to regional scales. This work integrates quantitative approaches to understand human-environment interactions and ecological transformations. While no specific scientific awards are documented in the source material, his leadership positions in major research consortia reflect significant professional recognition. He actively supervises doctoral candidates including Farina de Waard, whose research examines peatland degradation in northern Germany using spatiotemporal remote sensing techniques. Current projects such as EnMAP-Box and ReWetSpec demonstrate applied research in environmental monitoring, supported through institutional frameworks and partnerships like the Deutsche Bundesstiftung Umwelt scholarship funding. The Earth Observation and Geoinformation Science Lab (formerly Remote Sensing and Geoinformation Processing Working Group) operates as a multidisciplinary research hub developing advanced methodologies for environmental assessment. The team implements machine learning algorithms and sophisticated learning strategies to enhance accuracy and temporal robustness in land cover classification, with field-based validation components integrated into advanced teaching modules.

Erchan Aptoulaمشاهده پروفایل

استاد

• Digital Image Analysis
• Computer Vision
• Remote Sensing
• +۳ مورد دیگر

Erchan Aptoula is a Professor of Computer Science at Sabanci University's Faculty of Engineering and Natural Sciences in Istanbul, Türkiye. He is affiliated with the Computer Vision and Pattern Analysis Laboratory (VPALab) and actively conducts research in digital image analysis, computer vision, and deep learning with a focus on remote sensing and (bio)medical data. University: Sabanci University School: Faculty of Engineering and Natural Sciences Academic Rank: Professor Email: erchan.aptoula@sabanciuniv.edu His research interests span domain generalization for remote sensing, explainable AI, medical image analysis, and precision agriculture applications. Recent work includes advancements in open-set domain generalization for hyperspectral classification, pollen classification with novel datasets, and domain adaptation techniques for SAR flood segmentation. Scientific contributions include 15+ recent publications addressing domain generalization, semantic segmentation, and uncertainty quantification in remote sensing and medical imaging. Awards include 2nd place at IEEE SIU'25 student paper awards. Projects involve international collaborations with institutions in Tunisia, Finland, and the UK, focusing on medical image understanding, crowd counting, and Ottoman document analysis.

• Spatial Analysis
• Geographic Information Systems (GIS)
• Environmental Management
• +۵ مورد دیگر

Colin John McClean is a Senior Lecturer in the Department of Environment and Geography at the University of York , with over 25 years of experience in spatial analysis and GIS applications for environmental management. His career spans post-doctoral research at Cardiff and Newcastle, followed by academic roles at York since 1996. Education: BSc in Geography from the University of Edinburgh (1986); PhD in Geography from Durham University (1991). McClean’s research focuses on leveraging spatial datasets to address conservation ecology, climate change impacts on biodiversity, and land use modeling. He has pioneered work using machine learning methods like genetic algorithms and simulated annealing for reserve selection, with applications in the Sahel region (e.g., Shea Tree climate modeling) and marine conservation. Recent publications highlight interdisciplinary themes, including urban green-blue spaces and health , tropical peatland restoration , and oil palm sustainability . His work has been funded by NERC, Defra, EU, and the Darwin Initiative, often involving cross-institutional collaborations. He supervises PhD students in topics such as water chemistry prediction , soil nitrogen dynamics , and protected area effectiveness under climate change . No scientific awards are documented, but his research on climate change impacts has influenced major reports like the Stern Review and the 2007 IPCC assessment.

• Astronomy
• Astrophysics
• Machine Learning
• +۵ مورد دیگر

Robert Brunner serves as Professor of Astronomy at the University of Illinois at Urbana-Champaign, where he bridges astrophysical research with computational innovation. His work focuses on extracting knowledge from massive astronomical datasets through advanced statistical and machine learning techniques, while also extending methodologies to finance and agricultural applications. Research interests center on developing machine learning algorithms (random forests, deep neural networks, Bayesian estimation) for astronomical data analysis, cosmological parameter constraints via n-point clustering measurements, and hardware acceleration using GPUs/cloud systems. His interdisciplinary approach spans source classification, transient phenomena detection in surveys like SDSS and DES, and applications in financial time-series analysis and agricultural remote sensing. Recent publications (2019-2025) reveal strong cross-domain expertise: astronomical catalogs for Rubin Observatory and Spitzer surveys coexist with financial market analysis using community detection methods and agricultural computer vision systems. Key methodological threads include spatio-temporal forecasting, multimodal learning for earnings calls, and anomaly detection via extended isolation forests, demonstrating consistent innovation in handling petascale datasets across scientific boundaries.

Stephanie Wernerمشاهده پروفایل

استاد

• Comparative Planetology
• Planetary Dynamics
• Exoplanet Systems
• +۵ مورد دیگر

Stephanie Werner is a Professor at the University of Oslo's Department of Geosciences and serves as Co-Centre Leader of the Centre for Planetary Habitability since 2023. She has held various significant positions including Director of the Norwegian Research School for Dynamics and Evolution of Earth and Planets (2016-2024) and Team Leader of Earth and Beyond/Comparative Planetology at the Center for Earth Evolution and Dynamics (2013-2023). Her educational background includes: Dr. rer. nat. (PhD) from Free University of Berlin, Germany (2005) with thesis: "Major Aspects of the Chronostratigraphy and Geologic Evolutionary History of Mars" Diplom in Geophysics from the University of Kiel, Germany (1999) Professor Werner's research focuses on comparative planetology, planetary dynamics, exoplanet systems, and planetary geophysics . Her work spans the formation and evolution of planets and planetary systems, cratering chronology and processes, remote sensing of Earth and planets, and potential field data interpretation. She has made significant contributions to understanding the geological evolution of Mars, lunar cratering chronology, and the dynamics of planetary systems. Her recent publication trends reveal a strong focus on cratering chronology across solar system bodies , with particular attention to the Moon, Mars, and outer solar system satellites. She has led important revisions to lunar cratering chronology models and has investigated impact rates on Jupiter's, Saturn's, and Uranus' moons. Another major theme is the study of exoplanets around K-dwarf stars , examining their composition and formation processes. Her work also includes significant contributions to Mars exploration , particularly through the Planetary Terrestrial Analogues Library project supporting the ExoMars mission. Professor Werner holds several prestigious appointments: Co-Lead, ESA - Ariel Science Team Norwegian representative and Co-I, ESA - PLATO Consortium Member of the European Space Agency's ExoMars Rover Science Operations Working Group Member of the ESA - NASA Mars Sample Return Science Planning Group EGU Division President of Planetary and Solar System Sciences (2017-2021) She has supervised numerous students through the Norwegian Research School for Dynamics and Evolution of Earth and Planets, which she directed from 2016-2024. Her research has been supported by multiple grants from the European Space Agency and Norwegian research councils, enabling participation in major space missions including ExoMars, PLATO, and Ariel. Professor Werner leads the Planetary Terrestrial Analogues Library (PTAL) project, which provides crucial support for Mars missions by creating a comprehensive database of terrestrial analogues for Martian environments. She also contributes to the Mars Missions Analogue Sample Library (MM ASL) and the CRATER CLOCK project focused on calibrating cratering chronometers for planetary evolution studies.

Christopher Hassallمشاهده پروفایل

دانشیار

• Entomology
• Mimicry
• Camouflage
• +۸ مورد دیگر

Dr. Christopher Hassall is an Associate Professor of Animal Biology at the School of Biology, University of Leeds , with research spanning entomology, climate change impacts, urban ecology, and conservation science. He leads the Hassall Lab and the BioDAR Project , which uses weather radar for biodiversity monitoring. Research Interests Quantifying insect abundance via weather radar (BioDAR/PestDAR/DRUID projects) Urban freshwater ecosystems and socio-ecological dynamics Evolution of insect camouflage/mimicry and flight behavior Climate change impacts on pollinators and invasive species Shadow diversity and extinction studies (Leverhulme DTP Co-Director) Scientific Awards Fellow of the Higher Education Academy Fellow of the Royal Entomological Society Advising : Supervises postgraduate researchers including Sicily Fiennes , Isabella Flowers , and Mx Solanum Foulstone , with a focus on interdisciplinary extinction studies and urban entomology.

• Polar Science
• Arctic Marine Ecology
• Fisheries Management
• +۳ مورد دیگر

Ole Arve Misund serves as a Professor at the Norwegian Fisheries College within UiT The Arctic University of Norway, Tromsø. His research spans polar science, Arctic marine ecology, fisheries management, and international relations in polar regions, with particular focus on Norway-Russia scientific cooperation dynamics following geopolitical shifts in 2022. His research interests center on climate change impacts on Arctic marine ecosystems, acoustic monitoring of marine organisms, and the geopolitical dimensions of polar research. Recent work examines boreal species migration into the Central Arctic Ocean, machine learning applications for backscatter analysis, and management frameworks for the Central Arctic Ocean. Analysis of his recent publications reveals strong interdisciplinary trends, integrating marine ecology with political science through studies of Russian-Norwegian scientific collaboration under sanctions, illegal fishing enforcement, and policy-relevant polar research. His work consistently bridges academic research with practical fisheries management and geopolitical considerations. Misund actively engages in science communication through Norwegian media outlets like Nordlys and Fiskeribladet, addressing topics from climate policy contradictions to Antarctic hydrological changes. His expeditionary work includes North Pole 2022 aboard the "Kronprins Haakon" research vessel. Professional activities demonstrate significant leadership in polar research infrastructure development and international scientific collaboration, particularly through the Norwegian Polar Institute where he contributes to strategic planning and policy advice. His work emphasizes evidence-based approaches to Arctic governance amid evolving geopolitical landscapes.

Bashir Kazimiمشاهده پروفایل

پژوهشگر

• Deep Learning
• Computer Vision
• Materials Science
• +۳ مورد دیگر

Dr.-Ing. Bashir Kazimi is a group leader at the Materials Data Science and Informatics (IAS-9) department within the Institute for Advanced Simulation at Forschungszentrum Jülich. His work focuses on advancing deep learning and computer vision techniques for electron microscopy data analysis, enabling efficient material characterization. Expertise: Deep Learning, Computer Vision, Image Analysis Collaboration: Works closely with the Ernst-Ruska-Center (ER-C) for electron microscopy expertise Research Interests: Bashir develops and applies deep learning methods for tasks such as denoising, super-resolution, semantic segmentation, and tracking in electron microscopy. His applications span nanomaterial characterization, crystallographic defect identification, and orientation mapping. Scientific Trends: His recent publications highlight advancements in self-supervised learning, semantic segmentation of TEM images, and applications of deep learning to both materials science and archaeological monument detection in geospatial data. Scientific Achievement: Admitted to the Young Excellent Scientist Program (YESP) in 2024, supporting leadership development and scientific visibility Advising: Supervises Shrindhi Bhat , a PhD student in his group. He is involved in projects like FAST-EMI (Deep-learning assisted fast in situ 4D electron microscope imaging), with a focus on enhancing materials analysis through AI.

Caroline Margaux Gevaertمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۷ مورد دیگر

Caroline Margaux Gevaert serves as Associate Professor in the Department of Geo-information Processing at the University of Twente's Faculty of Geo-Information Science and Earth Observation (ITC), while also holding an appointment at the Digital Society Institute. Her academic career spans geospatial information systems, remote sensing, and the ethical applications of AI in geographical contexts. Dr. Gevaert earned her PhD in Informal Settlement Mapping with Unmanned Aerial Vehicles from the Faculty of Geo-Information Science and Earth Observation (ITC) in 2018, following Master's degrees in Geospatial Information Systems from Lund University (2014) and Remote Sensing from Universitat de Valencia (2013), and a Bachelor's in International Land and Water Management from Wageningen University & Research (2011). Her research focuses on the intersection of artificial intelligence and geospatial science, with particular emphasis on ethical dimensions of AI, algorithmic fairness in geo-intelligence workflows, and applications of machine learning for environmental monitoring. She has developed expertise in UAV applications for informal settlement mapping and flood vulnerability assessment, bridging technical innovation with societal impact. Analysis of her recent publications reveals a strong trend toward addressing ethical challenges in geospatial AI, with increasing focus on algorithmic fairness, explainable AI systems, and accountability frameworks. Her work demonstrates a consistent evolution from technical remote sensing applications toward socio-technical systems that consider both technological capabilities and societal implications. PhD Cum Laude (2018) Professor J.M. Tienstra Onderzoeksprijs 2020 Student Paper Competition Finalist (2017) Dr. Gevaert serves as Chair of De Jonge Akademie (2022-2027) and the International Society for Digital Earth (ISDE), while participating in the Frontier Technology Livestreaming Programme. Her external engagement includes consultancy for the World Bank and presentations on accountability in digital humanitarianism, demonstrating her commitment to applying geospatial intelligence for global development challenges. Her research activities center around geo-intelligence workflows, with particular focus on developing accountable and fair AI systems for spatial analysis. Current projects investigate causality frameworks for bias detection in flood vulnerability assessments and explainable workflows for ecological monitoring, positioning her at the forefront of ethical geospatial AI research.

• Statistics
• Categorical Data Analysis
• Survey Methodology
• +۳ مورد دیگر

Thomas Suesse is a Senior Lecturer at the School of Mathematics and Applied Statistics, University of Wollongong, with a career spanning institutions in Germany, New Zealand, and Australia. His academic journey includes a M.Sc. in Mathematics from Friedrich-Schiller-University Jena (2003) and a PhD in Statistics from Victoria University of Wellington (2008). Education: M.Sc. in Mathematics (FSU Jena, 2003), PhD in Statistics (VUW, 2008) His research focuses on Statistics, particularly Categorical Data Analysis, Social Network Modeling, and Spatial Statistics. Recent work explores variational Bayes inference for spatial autoregressive models, environmental extreme value detection algorithms, and the impact of missing data in statistical models. His publications span topics in public health, environmental science, and educational methodology. Key trends in his 15 most recent articles (2021-2025) include advancements in spatial statistics, applications of social network analysis to finance, and educational research comparing laboratory teaching objectives. He has also contributed to understanding pandemic effects on child health and activity patterns. Scientific Awards: 2008 VUW PhD thesis submission award; 2005-2008 VUW Postgraduate Scholarship. Thomas co-supervises PhD students on topics like spatial autoregressive modeling with missing data and variance estimation in mixture models. He has secured internal grants for computational infrastructure upgrades and studies on child movement behaviors. His professional affiliations include the Statistical Society of Australia.

Xiaoguang Dongمشاهده پروفایل

استادیار

• Medical Robotics
• Soft Robotics
• Swarm Robotics
• +۴ مورد دیگر

Dr. Xiaoguang Dong is an Assistant Professor in the Department of Mechanical Engineering at Vanderbilt University , School of Engineering. He received his Ph.D. (2019) and M.S. (2016) from Carnegie Mellon University, and B.S. (2013) from Harbin Institute of Technology. His research focuses on miniature soft robotics , swarm robotics , and intelligent soft materials for biomedical, microfluidic, and biomechanical applications. Design of shape-morphing soft robots for minimally invasive medicine Development of magnetic microrobot swarms for cooperative tasks Integration of machine learning with mechanics for smart material design Recent publications highlight advancements in wireless medical robots for drug delivery, biofluid pumping, and tissue sensing, with works in Science Advances , Nature Communications , and PNAS . He has received significant recognition including the 2025 NSF CAREER Award and 2024 Med-X Young Investigator Award . 2022 Spring: Dynamics (ME 2190) 2023 Fall: Miniature Robotics 2014-2015: Teaching assistant at Carnegie Mellon University

YongJiang Zhangمشاهده پروفایل

دانشیار

• Plant Physiology
• Climate Change
• Environmental Stress Physiology
• +۳ مورد دیگر

Dr. YongJiang (John) Zhang is an Associate Professor of Plant Physiology at the School of Biology and Ecology, University of Maine . His research focuses on plant responses to environmental stresses and climate change, particularly in wild blueberries and trees. His lab uses interdisciplinary approaches including field studies, UAV sensors, and controlled experiments. Dr. Zhang holds a Ph.D. from the University of Miami (2012) and Chinese Academy of Sciences (2011). Education: Ph.D., University of Miami, 2012 Ph.D., Chinese Academy of Sciences, 2011 Research Interests: Plants' physiological and structural adaptations to climate change, including water transport mechanisms, drought tolerance, and carbon balance. Key themes include wild blueberry resilience in Maine, tropical tree physiology, and precision agriculture techniques like UAV-based monitoring. His work integrates multi-scale approaches from lab experiments to ecosystem-level modeling. Lab & Collaborations: The Zhang Lab is located in Murray Hall and Hitchner Hall. Current research includes wild blueberry climate resilience, water-use efficiency of Maine forests, and novel technologies for crop management. Dr. Zhang collaborates with institutions like Harvard University and the Climate Change Institute. Grants & Advising: Oversees multiple graduate students and undergraduate researchers. Recent projects include NSF-funded studies on climate impacts and USDA grants for precision agriculture. Advises on topics like UAV applications and drought resistance genetics.

Mario Harperمشاهده پروفایل

استادیار

• Machine Learning
• Data Science
• Robotics
• +۲ مورد دیگر

Mario Harper is an Assistant Professor in the Department of Computer Science at Utah State University. His research emphasizes Machine Learning, Data Science, Robotics, and their intersections with Finance and Artificial Intelligence. He specializes in autonomous systems, energy-efficient robotics, and AI-driven solutions for transportation and urban sustainability. His work includes developing tools like simulators for electric vehicle systems and stealth-centric navigation algorithms inspired by biological systems. Key research areas include multi-robot coordination, reinforcement learning applications in robotics, and algorithmic approaches to environmental and economic challenges. He has contributed to projects like POSEIDON-SAT for satellite-based fishing vessel detection and electrified transportation equity analysis in urban settings. His publications span topics from trajectory planning in legged robots to AI modeling for economic systems. Beyond research, he designs interactive visualization tools to support policy decisions on sustainable transportation infrastructure. No scientific awards are explicitly listed in the provided information. Mario Harper’s advising and grants focus on robotics, energy systems, and AI applications, though specific student advisees or grant details are not detailed here. He collaborates on projects involving lab tools such as the Unknown Building Exploration Simulator (UBES) and Stealth Centric Autonomous Robot Simulator (SCARS), advancing robotic autonomy in unstructured environments.

Jonathan E. Martinمشاهده پروفایل

استاد

• Synoptic Meteorology
• Atmospheric Dynamics
• Jet Stream Variability
• +۳ مورد دیگر

Jonathan E. Martin is a Professor in the Department of Atmospheric and Oceanic Sciences at the University of Wisconsin–Madison since 1994. He received his Ph.D. in Atmospheric Sciences from the University of Washington in 1992. Research Focus: Mid-latitude cyclones, jet stream dynamics, and weather-climate interactions Key Methods: Multi-scale observational analysis, high-resolution mesoscale modeling, potential vorticity diagnostics Recent Projects: Jet stream waviness trends, subtropical-midlatitude cyclone transformation, snow cover-cyclone feedback His 2025-2024 publications examine extratropical cyclone precipitation distribution, Pacific basin rapid cyclogenesis, and Earth system model validation for cyclone occlusion. Earlier work (2023-2019) addresses: Jet superposition climatology Self-organizing map analysis of jet variability Cyclone-induced Southern Hemisphere waviness Nonlinear jet retraction mechanisms Tornado outbreak jet influences Historical cold pool contraction trends Awarded the 2021 Atmospheric Sciences Librarians International Choice Runner Up for his historical meteorology work, he also authored the textbook Mid-Latitude Atmospheric Dynamics: A First Course (2013). His research spans cyclogenesis, frontogenesis, and climate change impacts on jet streams, with applications in extreme weather forecasting and climate modeling validation.

Khaled Sobhanمشاهده پروفایل

استاد

• Geotechnical Engineering
• Pavement Materials/Design
• Geosynthetics
• +۳ مورد دیگر

Professor Khaled Sobhan is affiliated with the Department of Civil, Environmental and Geomatics Engineering at Florida Atlantic University . His research focuses on geotechnical engineering, pavement design, and sustainable materials. Education: Ph.D. from Northwestern University His work includes studies on soil stabilization, geosynthetic reinforcement, and fatigue analysis of recycled construction materials. Recent projects involve InSAR-based subsidence monitoring and seismic stability of retaining walls. Key trends in his publications (2025–2020) include applications of artificial neural networks in foundation analysis, geosynthetic contributions to pavement durability, and marine corrosion resistance of geopolymer concrete. His lab specializes in geotechnical testing for coastal infrastructure resilience.