جست‌وجوی استاد و پژوهشگر

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.

• Spatial Data Infrastructure (SDI)
• GIS Applications
• Machine Learning in Geoinformatics
• +۳ مورد دیگر

Iwona Kaczmarek is a Professor in the Department of Systems Research at the Wrocław University of Science and Technology's Faculty of Spatial Management and Landscape Architecture. Her work focuses on advancing spatial data infrastructure (SDI), geoinformatics, and machine learning applications in urban and regional planning. She leads interdisciplinary research integrating GIS, natural language processing (NLP), and graph neural networks to address challenges in spatial planning, policy analysis, and socio-economic modeling. Research interests include: Spatial data integration and interoperability Machine learning for geospatial analysis Semantic web technologies for open data Urban sustainability and transit-oriented development Policy text mining and stakeholder analysis Recent work emphasizes: 1. Combining media sentiment analysis with economic indicators during crises (2025) 2. GeoAI-driven quality of life predictions using graph neural networks (2023) 3. Knowledge graph extraction from spatial development plans (2023) 4. Harmonizing local planning documents via NLP (2022) Collaborations include projects like the EYE initiative analyzing remote sensing for economic trends and SDI implementations in academic contexts. Over 75 documented outputs highlight her contributions to geospatial innovation and policy-relevant research.

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.

Amy Roseمشاهده پروفایل

پژوهشگر

• Geographic Information Systems (GIS)
• Transportation Geography
• Environmental Science
• +۴ مورد دیگر

Amy Rose is a Senior Staff Scientist at Oak Ridge National Laboratory (ORNL), specializing in geospatial science and human security. She earned her B.A. and M.S. in Geography from the University of Tennessee (UTK), followed by a Ph.D. in Geography (part-time while working full-time). Her career spans over two decades, with roles at the UT Center for Transportation Research (UTCTR), The Shaw Group, and ORNL. She is a key contributor to the LandScan project, developing global population estimates, and leads interdisciplinary research in spatiotemporal modeling of human dynamics. Education: B.A. (UTK), M.S. (UTK with minor in Logistics & Transportation), Ph.D. (UTK Geography) Research Focus: GIS applications in transportation, environmental site assessment, population modeling, and GeoAI. Professional Highlights: Technical lead for Defense Logistics Agency projects, co-developer of LandScan, and advocate for open geospatial data. Her work emphasizes leveraging geospatial tools to address complex challenges, including environmental remediation and global population dynamics. She has collaborated closely with federal agencies like the National Geospatial-Intelligence Agency (NGA) to advance open data initiatives.

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.

Shih Lung Shawمشاهده پروفایل

استاد

• Transportation Geography
• Geographic Information Science
• Spatio-temporal Analysis
• +۳ مورد دیگر

Shih Lung Shaw is Chancellor's Professor and Professor in the Department of Geography at the University of Tennessee, Knoxville, with affiliations to the Center for Transportation Research. His research integrates transportation geography, geographic information science (GIScience), and spatiotemporal analysis to study human activity patterns, mobility behaviors, and transportation systems. Shaw's work focuses on developing analytical frameworks for understanding human dynamics in physical-virtual environments, applications of GIS in transportation (GIS-T), and the effects of information technologies on travel behaviors. Recent projects examine urban mobility during the COVID-19 pandemic and theoretical frameworks for cyber victimization risk in hybrid spaces. He has published extensively on human mobility patterns using emerging data sources like mobile phone location data. Shaw's methodological innovations include advancements in time geography, space-time GIS, and spatiotemporal analytics. His research contributes to smart city development and sustainable transportation planning.

Emmanuel Stefanakisمشاهده پروفایل

استاد

• Geospatial Data Science
• Digital Earth
• Discrete Global Grid Systems (DGGS)
• +۱۷ مورد دیگر

Emmanuel Stefanakis is a Professor and Department Head of Geomatics Engineering at the Schulich School of Engineering, University of Calgary. He holds a PhD in Electrical and Computer Engineering (National Technical University of Athens, 1997), an MScE in Geodesy and Geomatics Engineering (University of New Brunswick, 1994), and a Dipl.Eng in Rural and Surveying Engineering (National Technical University of Athens, 1992). His research focuses on Geospatial Data Science, Discrete Global Grid Systems (DGGS), GeoAI, and applications of Geomatics in natural hazards, transportation, and climate change . He has led over 140 student projects and authored/co-authored five textbooks and 150+ articles. Notable awards include the 2023 Canadian Cartographic Association’s Award of Distinction and the 2023 UCalgary Teaching Excellence Award. Recent articles emphasize high-performance trajectory analysis, DGGS integration, and geospatial quantum computing . His work bridges theoretical advancements with practical tools for flood modeling, epidemiology, and urban planning. Grants include NSERC Discovery Grants and collaborations with industry partners like McElhanney Ltd. Professional memberships span the Canadian Institute of Geomatics, Canadian Cartographic Association, and APEGA. He served as Editor-in-Chief of Cartographica (2014–2022) and actively contributes to international conferences on geoinformatics. His educational initiatives include innovative course designs in online and distance learning. Current roles include leadership in the HALOS and Geospatial Quantum Computing projects, advancing geomatics engineering education in the digital era.

• Aging and Health
• Population Studies
• Development Studies
• +۵ مورد دیگر

Qiushi Feng is an Associate Professor at the National University of Singapore , Department of Sociology, with a focus on aging and health, population studies, and development research. He holds administrative roles as Deputy Head of Department and Assistant Dean at the Faculty of Arts and Social Sciences. PhD from Duke University Co-Editor of Current Sociology , Associate Editor of Asian Population Studies Recipient of grants from United Nations Population Fund, Singapore Ministry of Education, and National Medical Research Council His research spans interdisciplinary aging studies, including digital equity, environmental health impacts, healthcare policy, and population projections. Recent publications analyze marital transitions in Indonesia, spatial healthcare optimization in Singapore, and pandemic impacts on life expectancy. Key trends in his work include: Interdisciplinary aging research Probabilistic population projections Age-friendly urban design Health equity in digital and environmental contexts

Kenny Josephمشاهده پروفایل

دانشیار

• Computational Social Science
• Social Inequality
• Machine Learning
• +۹ مورد دیگر

Kenny Joseph is an Associate Professor in the CSE Department at the University at Buffalo, leading the Computation and Equity Lab (cubelab) . His work bridges computational methods with social inequality research, focusing on predictive modeling for social good and analyzing systemic disparities through digital traces. Current affiliation: University at Buffalo Previous positions: Postdoc at LazerLab (Northeastern), Fellow at Harvard's Institute for Quantitative Social Science Research Interests: Combining machine learning with social theory to address structural inequalities in areas like foster care systems, neighborhood change, and gender disparities in academia. Key methodologies include agent-based modeling, network analysis, and large-scale data mining. Publication Trends: Recent work focuses on Social media dynamics and misinformation Equity-focused predictive modeling Political communication analysis Identity expression in digital spaces Urban planning applications Additional Contributions: Developer of computational tools for location extraction (GALLOC) and self-presentation analysis, with applications in disaster response and social inequality research.

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.