جست‌وجوی استاد و پژوهشگر

Antonio Medranoمشاهده پروفایل

استادیار

• Geospatial Computing
• GeoAI
• UAV Swarms
• +۱۰ مورد دیگر

Antonio Medrano is an Assistant Professor of Geospatial Computer Science at Texas A&M University–Corpus Christi (TAMUCC) and the director of the Geospatial Optimization & Analytics Lab (GOAL). His research focuses on location optimization, spatial logistics, high-performance computing (HPC), and artificial intelligence/machine learning (AI/ML) with applications to drone systems, coastal environmental science, and facility location modeling. Specializations: Geospatial Computing, GeoAI, UAV Swarms, Remote Sensing, HPC, Parallel Computing, Big Data, Spatial Optimization, Multi-Objective Optimization, GIS. Labs: Geospatial Optimization & Analytics Lab (GOAL). Students: Mona Hajiesmaeeli, Gabriel Nambila, Abhishek Phadke, Marina Vicens Miquel (all graduated). His work emphasizes fast optimization algorithms, parallelization of network algorithms for HPC resources, and generating diverse near-optimal solutions. He is affiliated with the AI2ES NSF Institute, contributing to AI-driven coastal inundation prediction and resilient cyber-physical systems.

Varuni Jayasooriyaمشاهده پروفایل

استادیار

• Geospatial Artificial Intelligence (GeoAI) for Green and Smart Cities
• Data-Driven Urban Sustainability
• Urban Microclimates
• +۲ مورد دیگر

Varuni Jayasooriya is an Assistant Professor at the School of Environment and Sustainability (SENS), University of Saskatchewan. Her research focuses on Geospatial Artificial Intelligence (GeoAI), urban sustainability, and the interplay between urban design and microclimates. She holds a PhD in Environmental Engineering from Victoria University, Australia, and a BSc in Earth Resources Engineering from the University of Moratuwa, Sri Lanka. Research Interests Dr. Jayasooriya explores innovative solutions for green and smart cities through data-driven approaches. Her work addresses urban heat islands, microclimate dynamics, and the role of green infrastructure (e.g., trees, green roofs) in enhancing thermal comfort. Recent studies include tropical urban canyon thermal environments and pavement material impacts on urban climates. Publications Her recent works (2021–2024) span urban climate modeling, green infrastructure efficacy, and smart city technologies. Key themes include GeoAI applications, sustainable rooftop technologies, and tropical urban bioclimatic adaptations. Professional Activities No specific grants or awards listed. She is affiliated with SENS and contributes to interdisciplinary urban sustainability research.

Shenghua Gaoمشاهده پروفایل

دانشیار

• Spatio-temporal Data Analysis
• Machine Learning
• Database Systems
• +۴ مورد دیگر

Professor Shenghua Gao is an Associate Professor at the School of Computing and Data Science of the University of Hong Kong (HKU), concurrently serving as Assistant Director for Shanghai Initiatives. He holds a PhD from Nanyang Technological University. His research focuses on integrating machine learning, spatio-temporal data analysis, and database systems to address challenges in mobility prediction, traffic management, and geospatial representation learning. He has contributed significantly to trajectory modeling, indexing frameworks for multi-dimensional data, and the application of large language models (LLMs) in spatio-temporal contexts. Key research interests include: Spatio-Temporal Data Science: Developing frameworks for efficient processing and analysis of point cloud, trajectory, and traffic data. Machine Learning for Databases: Innovating indexing algorithms (e.g., BMTree, MAST) and query optimization techniques leveraging ML. Trajectory and Mobility Prediction: Creating personalized models for next-location prediction and transfer learning across regions. Geographic AI (GeoAI): Enhancing road network representation and urban function inference using physics-guided and foundation models. Recent work highlights include the ST-LLM+ framework for traffic prediction, the MAST system for point cloud analytics, and the exploration of City Foundation Models for urban challenges. His publications span top venues in databases (SIGMOD, VLDB) and AI/data science (ICML, NeurIPS). While no awards are explicitly mentioned, his prolific output and leadership roles indicate significant academic contributions. He is actively involved in teaching and supervising research in the School’s undergraduate and postgraduate programs, including MSc(AI) and MPhil/PhD tracks.

Johannes Scholzمشاهده پروفایل

استاد

• Geospatial Artificial Intelligence (GeoAI)
• Geospatial Knowledge Graphs
• Semantics and Ontologies in Geography
• +۱۲ مورد دیگر

Johannes Scholz is a Full Professor for Geoinformatics at the Department of Geoinformatics (Z_GIS) at Paris-Lodron-University Salzburg. He leads the GeoAI, GeoKG, and GeoSemantics research group and holds secondary roles in academic governance, including membership in the Curricularkommission Geographie at Salzburg and the Austrian Standards TC 084 committee. He has held visiting positions at the University of California, Santa Barbara, and prior affiliations include Associate Professor at Graz University of Technology and Senior Researcher at Research Studios Austria - Studio iSPACE. His research interests span geospatial artificial intelligence, knowledge graphs, semantics, and numerical optimization, with applications in energy transition, digital tourism, and cyber-physical systems. Projects include Agent-based simulation for energy systems GeoHumanities integration Indoor geography analysis Selected scientific awards include the ISPRS Outstanding Reviewer Award (2020) and the Forschungspreis der Steiermark (2011). He has secured significant funding for projects such as "Virtual Shepherd" (FFG 2024) and "ABM4EnergyTransition" (FFG 2022).

• Geospatial Big Data Analytics
• GeoHealth
• GeoAI (Geospatial Artificial Intelligence)
• +۷ مورد دیگر

Tao Hu is an Assistant Professor in the Department of Geography at Oklahoma State University (OSU), serving since 2021. He holds a PhD (2015) and BS (2009) in Geography from Wuhan University, China. Prior to OSU, he worked as a Postdoctoral Research Fellow at Harvard University's Center for Geographic Analysis (2019–2021) and Kent State University (2016–2019). Research Focus: Leverages geospatial big data (remote sensing, social media, smartphone mobility) and GeoAI models to address health disparities, environmental health, and urban sustainability challenges. Key Contributions: Over 60 peer-reviewed articles, including 5 ESI Highly Cited Papers (top 1%). Research supported by NSF, USDA, and ESIP. His work spans FAIR workflow systems, disaster public perception analysis (e.g., Ohio train derailment), heat vulnerability modeling, and healthcare accessibility via mobility data. He emphasizes reproducible GIScience and societal impact through actionable insights. Teaching includes courses on GIS in public health, health geography, and programming for geospatial applications. His lab integrates geospatial AI with health equity, environmental justice, and smart city initiatives.

Heng Caiمشاهده پروفایل

استادیار

• Geographic Information Science
• Disaster Resilience
• Socio-Environmental Sustainability
• +۳ مورد دیگر

Dr. Heng Cai is an Assistant Professor at Texas A&M University, leading the GIScience for Resilience (GIResilience) Research Group. Her work focuses on geographic information science, disaster resilience, socio-environmental sustainability, and environmental health. She develops geospatial data mining and decision-support tools to model human-environment interactions under climate change and natural hazards. Education: Ph.D. in Environmental Science (Louisiana State University), M.S. in Geographic Information Science (Chinese Academy of Sciences), B.E. in Surveying and Mapping (China University of Geosciences). Research interests include geospatial data science, hazard modeling, and resilience assessment. Her group has pioneered studies on land loss prediction in coastal Louisiana, social media analysis for disaster response, and cyberGIS platforms like PRIME. Recent work emphasizes climate adaptation strategies and urban resilience frameworks. Publications span interdisciplinary journals like Remote Sensing , Annals of the American Association of Geographers , and International Journal of Digital Earth . She actively collaborates with NASA and disaster management agencies, securing grants for projects like HeatSMART and U-CARE. Labs/Teams: GIResilience Group (www.gis-resilience.info) focuses on innovative geospatial solutions for societal resilience. She mentors undergraduate and graduate students in GIS programming, webGIS, and geodatabase applications.

Christopher Shafferمشاهده پروفایل

مدرس

• Geospatial Technologies
• Environmental Science
• Sustainability
• +۵ مورد دیگر

Christopher Shaffer is a GIS Manager and Instructor in the Environmental Science & Sustainability Department at Allegheny College. He specializes in geospatial technologies, including GIS, GPS, remote sensing, and sUAS, to address environmental challenges. Education: B.S. in Geography with a GIS concentration and a minor in Information Systems from Clarion University of Pennsylvania (2000) With over 25 years of experience in digital geographic data management and analysis, Shaffer focuses on GIS-based multicriteria evaluation techniques such as Boolean logic, weighted linear combination, and fuzzy logic. His work emphasizes transforming geographic data into actionable information through advanced map manipulation and overlay methods in vector and raster environments. He teaches courses like Environmental GIS I/II , Independent Study , and Senior Project I/II , while managing the Carr Hall GIS lab. His technical expertise spans geodatabase design, geoprocessing modeling, image classification, and geospatial AI applications. Shaffer has held continuous roles at Allegheny College since 2000, progressing from GIS Laboratory Manager to his current dual position as GIS Manager/Instructor. He facilitates experiential learning through collaborations with local stakeholders.

Sven Lautenbachمشاهده پروفایل

استاد

• Land Use Change
• Ecosystem Services
• Environmental Modeling
• +۱۰ مورد دیگر

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

Suchendra M. Bhandarkarمشاهده پروفایل

استاد

• Artificial Intelligence
• Computer Vision
• Pattern Recognition
• +۴ مورد دیگر

Suchendra M. Bhandarkar is a Professor in the School of Computing at the University of Georgia, affiliated with the Franklin College of Arts & Sciences. He holds courtesy faculty positions in the College of Engineering and the School of Environmental, Civil, Agricultural, and Mechanical Engineering. His research focuses on Artificial Intelligence, Computer Vision, Pattern Recognition, and Computational Biology. He has advised PhD students such as Anirban Mukhopadhyay and has been actively involved in interdisciplinary projects spanning robotics, coral reef mapping, and food safety automation. Education: Ph.D. and M.S. in Computer Engineering from Syracuse University (1985-1989), and B.S. in Electrical and Electronics Engineering from Indian Institute of Technology Bombay (1983). His funded projects include advanced GeoAI terrain analytics, underwater robotics, and AI-driven food safety systems. Notable grants include support from USDA, NIH, and the US Army. Research highlights include 3D coral reef mapping via SLAM, deep learning for food safety, and zero-shot learning algorithms. Key collaborations involve the USDA Agricultural Research Service, Sony Corporation, and international networks like CapsNet for medical imaging. His labs and teams focus on applying AI to environmental, biomedical, and agricultural challenges.

• Geomatics
• Cultural Heritage Digitization
• 3D Modeling and Reconstruction
• +۷ مورد دیگر

Francesca Matrone is a Fixed-term Assistant Professor in the Department of Environment, Land and Infrastructure Engineering (DIATI) at Politecnico di Torino, Italy. Her work bridges geomatics, artificial intelligence, and cultural heritage conservation, with a focus on 3D modeling, GIS, and HBIM integration for urban and historical environments. Her research interests include Geomatics, Cultural Heritage Digitization, AI in Geospatial Analysis, Drone-Based 3D Modeling, Semantic Segmentation of Point Clouds, and Smart Cities . She applies advanced technologies like UAVs, deep learning, and BIM-GIS integration to enhance the documentation, maintenance, and resilience of built heritage. The recent publications highlight a strong trend in using AI and machine learning for semantic segmentation of 3D heritage models, integration of HBIM with GIS using standards like IFC and CityGML, and drone-based photogrammetry for urban and territorial planning. These works reflect a multidisciplinary approach combining computer science, civil engineering, and digital heritage. Francesca Matrone is actively involved in research projects such as: HERITALISE (2025–2028, EU-funded): Digitization and cloud visualization of heritage buildings ACLIMO (2024–2026): Research collaboration with APAM on protected areas COGNITIO-FORT (2025–2026): Scientific Director for a project with Unione Montana Valle Stura She teaches across multiple programs: PhD : GeoAI for advanced urban analyses; Drones for 3D modeling (Main Teacher) Master’s : GIS Modeling for City and Land; Knowledge of Built Heritage under Climate Change Bachelor’s : GeoAI: Artificial Intelligence and Geospatial Data; Topography (Course Collaborator) She is a member of the Teaching Colleges for Civil and Building Engineering and Electronic, Telecommunications and Physics Engineering. She also holds a Learning to Teach (L2T) Open Badge from Politecnico di Torino, demonstrating her commitment to pedagogical excellence. Francesca is a co-inventor of the MAIN10ANCE PLATFORM , a national software patent aimed at enhancing the maintenance and conservation of historical built heritage through integrated HBIM-GIS systems.

Orhun Aydinمشاهده پروفایل

استادیار

• Computational Sustainability
• Spatial and Spatiotemporal Artificial Intelligence (GeoAI)
• Urban Sensing
• +۶ مورد دیگر

Orhun Aydin is an Assistant Professor at Saint Louis University's School of Science and Engineering , affiliated with the Department of Earth and Atmospheric Sciences and Department of Computer Science (by courtesy) . Ph.D. in Energy Resources Engineering (Geostatistics), Stanford University M.Sc. in Computer Science, Georgia Institute of Technology M.Sc. in Energy Resources Engineering, Stanford University B.Sc. in Petroleum Engineering and Electrical/Electronic Engineering, Middle East Technical University His research spans computational sustainability, spatial artificial intelligence (GeoAI), urban sensing, and integrated human-earth system modeling, with applications in disaster response optimization and open-source geospatial software development. Recent publications focus on spatial clustering algorithms, seagrass habitat conservation modeling, and stochastic regionalization frameworks, reflecting interdisciplinary work at the intersection of geoscience, data science, and environmental management. He teaches courses on Machine Learning in GIS and Remote Sensing and Advanced Programming in GIS and Remote Sensing , leveraging his dual expertise in geospatial analysis and computational methods.

• GIS and Information Technologies in Planning
• Remote Sensing
• Photogrammetry
• +۷ مورد دیگر

Prof. Elif Sertel is a Professor of Geomatics Engineering at Istanbul Technical University's Faculty of Civil Engineering, specializing in GIS, Remote Sensing, and Satellite Technologies. She holds a PhD from ITU (2008) and has conducted groundbreaking research on land use analysis, urbanization impacts, and geospatial AI applications. Her work integrates historical aerial photography with modern satellite data to model environmental and demographic changes. Notable projects include the GeoAI_LULC_Seg ERC-funded initiative analyzing rural depopulation and agricultural land abandonment in Turkey and Bulgaria since 1940. She has led over 30 research projects totaling €6M+, with notable funding from TÜBA, ERC, and the Ministry of Development. Awards include the 2024 Istanbul Technical University Academic Performance Award and the 2017 TÜBA Outstanding Young Scientist Award. Her teaching includes GIS in Engineering courses. Research focuses on: 1) AI-driven land cover segmentation using deep learning, 2) drought monitoring via satellite data, 3) urban heat island analysis, and 4) landscape metric correlations with satellite resolution. Recent work emphasizes historical data integration, with projects like the 1958-2020 Bursa land use study. Her team developed benchmark datasets (VHRTrees, HRPlanes) and tools like the GeoAI-based mobile drought app. Grants and projects: Over 30 completed projects including €150k ERC GeoAI_LULC_Seg (2022-2024), €5M ITU Satellite Ground Terminal Renewal (2016-2020), and TÜBA-funded city mapping initiatives. Collaborations with institutions like NASA, ESA, and European Research Council have produced over 50 peer-reviewed publications. Awards highlight sustained excellence: 2023-2024 Academic Performance Awards, 2024 Broadcasting Achievement Award, and 2017 TÜBA recognition. Her work bridges geomatics engineering with environmental policy through interdisciplinary approaches.

Liping Yangمشاهده پروفایل

استادیار

• GIScience
• Geospatial Artificial Intelligence (GeoAI)
• Computer Vision
• +۶ مورد دیگر

Liping Yang is an Assistant Professor in the Department of Geography and Environmental Studies and the Department of Computer Science at the University of New Mexico (UNM). She also holds an affiliate faculty position at the Center for the Advancement of Spatial Informatics Research and Education (ASPIRE). Her research focuses on geospatial artificial intelligence (GeoAI), computer vision, and machine learning applied to geospatial big data analytics, disaster management, and indoor navigation. She directs the GeoAIR Lab, which develops innovative methods for GeoAI and geovisualization. Education: Ph.D. in Spatial Information Science and Engineering from the University of Maine (2015), M.S. in Cartography and GIS from Fujian Normal University (2009), and B.S. in GIS from Yunnan Normal University (2006). Postdoctoral positions at Los Alamos National Laboratory (LANL) and Penn State University. Research interests include GIScience, GeoAI, visual big data analytics, geovisualization, and indoor navigation. Her work emphasizes developing AI-driven solutions for smart cities, disaster management, and infrastructure monitoring. Awards: National Scholarship (China, 2004), Yunnan Province Government Scholarship (2005), Michael J. Eckardt Dissertation Fellowship (2014–2015), and Graduate Research Assistantship at University of Maine. Teaching includes courses on advanced GIScience, internet mapping, and geospatial statistics. Her students have developed interactive web maps for topics like water quality in the Navajo Nation and worldwide shark attacks. Labs/Teams: Directs the GeoAIR Lab, collaborating with institutions like LANL and Penn State. Active in organizing workshops on diagram image retrieval (DIRA) at CVPR.

Jin Sunمشاهده پروفایل

استادیار

• Computer Vision
• Machine Learning
• Deep Neural Networks
• +۷ مورد دیگر

Jin Sun is an Assistant Professor in the School of Computing and a faculty fellow at the Institute for Artificial Intelligence at the University of Georgia. He holds a Ph.D. in Computer Science from the University of Maryland, College Park (2018). His research focuses on computer vision and deep learning , particularly in understanding human behavior, 3D geometry, and applying AI to healthcare, agriculture, and societal challenges. He is a Lilly Teaching Fellow and actively collaborates across disciplines. Education: Ph.D. Computer Science, University of Maryland (2018) Affiliations: School of Computing, Institute for AI, Franklin College of Arts & Sciences His research interests include machine learning , generative models , object detection , and context modeling . Recent work spans precision agriculture (e.g., cotton boll analysis), healthcare AI (e.g., bed occupancy detection), and multimodal geospatial applications. Grants & Funding: NIH R21 Grant (PI, 2024) USDOT Grant (Co-PI, 2025) UGA Presidential Interdisciplinary Seed Grant (Co-PI, 2024) Google Inc. Sponsorship (2022–2024) Key Contributions: Developed frameworks for 3D scene reconstruction, AR-driven data collection systems, and benchmark datasets for zooplankton recognition and enzymatic function prediction. His work bridges AI with real-world applications in environmental science and healthcare.

Stef De Sabbataمشاهده پروفایل

دانشیار

• Geographical Artificial Intelligence (GeoAI)
• Urban Analytics
• Generative Artificial Intelligence
• +۳ مورد دیگر

Stef De Sabbata is an Associate Professor of Geographical Information Science at the University of Leicester, holding dual affiliations with the School of Geography, Geology and the Environment and the Institute for Digital Culture. She serves as Chair of the Geographic Information Science Research Group at the Royal Geographical Society and previously chaired GISRUK 2018. Her research focuses on GeoAI, urban analytics, and cultural informatics, with notable contributions to graph neural networks in geodemographic classification and urban form analysis. Education includes a PhD in Geography from the University of Zurich (2013), and BSc/MSc in Computer Science from the University of Udine. Prior to Leicester, she held roles at the Oxford Internet Institute (OII) including Researcher (2013-2015), Junior Research Fellow at Wolfson College (2014-2015), and Research Associate (2015-2021). Her work explores spatially-explicit approaches to urban systems and the application of large language models in geographic contexts. Professional roles include membership in the International Cartographic Association's Commission on Location-Based Services and leadership in interdisciplinary initiatives like the GeoNet project examining Sub-Saharan Africa's knowledge economies. No specific awards are explicitly listed in the provided materials.