جست‌وجوی استاد و پژوهشگر

Miklós Korenمشاهده پروفایل

استاد

• International Trade
• Economic Development
• Productivity Analysis
• +۵ مورد دیگر

Miklós Koren is a Professor of Economics at Central European University and Senior Research Fellow at the HUN-REN Centre for Economic and Regional Studies. His work bridges international trade , economic development , and managerial economics , focusing on trade policy, productivity spillovers, and the role of managers in development. Ph.D., Harvard University (2005) M.A., Central European University (2000) M.Sc., Budapest University of Economics (1999) His research explores trade facilitation , managerial impact on firm performance , and technological diversification . Recent work includes studies on expatriate managers, pandemic-related business disruptions, and the legacy of communist-era management practices. Key trends in his publications (2020–2024) emphasize managerial mobility and firm productivity (2024) machine learning vs. gravity models (2024) trade volatility and development (2023) data transparency standards (2022) Scientific awards include ERC Starting Grant (2012) Nicholas Káldor Prize (2014) Young Economist Award (2002, 2004) As Data Editor for Review of Economic Studies and Associate Editor for Journal of International Economics , he shapes methodological rigor in empirical research. His 2013 paper on technological diversification remains foundational for understanding volatility in developing economies.

• GIScience
• Cartography
• Geovisual Analytics
• +۳ مورد دیگر

Jennifer Mason is an Associate Professor of Practice and Associate Director of the Geographic Information Science & Technology (GIST) Program at the University of Arizona. She holds a Ph.D. in Geography (GIScience) from Penn State University, an M.S. in GIScience from San Diego State University, and a B.A. in Geography from UCLA with a GIS&T minor. Her research focuses on GIScience, cartography, and geovisual analytics, particularly exploring uncertainty visualization in maps and spatial decision-making. She teaches courses such as Web GIS, Geovisualization, and Raster/Vector Spatial Analysis, emphasizing practical applications of geographic information systems. Jennifer's work bridges theoretical research and pedagogy, with a strong emphasis on improving cartographic design and usability for diverse audiences. Her publications consistently address spatial uncertainty representation, cognitive aspects of geographic visualization, and open-source tools for education. She has contributed to advancing methodologies for visualizing spatial data uncertainty through noise annotation lines and thematic mapping techniques.

Robert P. Andersonمشاهده پروفایل

استاد

• Biogeography
• Species Distribution Modeling
• Biodiversity Conservation
• +۵ مورد دیگر

Robert P. Anderson is a Professor of Biology in the Division of Science at City College of New York (CCNY), part of the City University of New York (CUNY) system. His research laboratory is located in Marshak Science Building (Room 810), with additional affiliation as a Research Associate at the American Museum of Natural History (AMNH) Mammalogy Department. As a Highly Cited Researcher (2019-2023) and AAAS Fellow (2023), he leads an interdisciplinary biogeography research program focused on modeling species niches and distributions. Dr. Anderson's research spans biodiversity modeling, biogeography, and ecology with specialization in mammals. His lab develops ecological modeling software widely applied in conservation biology, invasive species management, zoonotic disease studies, and climate change impact assessments. Key research themes include: Characterizing spatial configuration of environmental suitability for species Developing machine learning approaches (particularly Maxent) for species distribution modeling Studying climate change effects on biodiversity Conservation applications of biogeographic models Neotropical mammal systematics and ecology His work has resulted in significant software contributions including Wallace, ENMeval, and spThin, with recent publications emphasizing methodological improvements in species distribution modeling and conservation applications. The lab maintains active projects funded by NASA and the National Science Foundation, focusing on small mammals of North and South America. Scientific recognition includes: AAAS Fellow (2023) Web of Science Highly Cited Researcher (2019-2023) Blavatnik Science Scholar (New York Academy of Sciences) Most Downloaded Paper in Ecography (2023-2024) Most Cited Paper in Ecography (2023) Dr. Anderson mentors graduate students through the CUNY Graduate Center and CCNY Master's programs, with recent advisees receiving prestigious awards including the ASM Horner Award and NASA FINESST Fellowship. His lab trains students in environmental biology through interdisciplinary research combining fieldwork, morphology, climatology, remote sensing, physiology, and genetics. Current lab members include Andrew Gaier (NASA Fellow), Mariano Soley-Guardia, and Kass (lead author on highly cited Wallace v2 paper). The Anderson Lab operates from CCNY's Marshak Science Building as part of the university's biodiversity group studying ecology, evolution, and geography of life on Earth. The lab emphasizes software co-design between end-users and developers to enhance conservation utility, with recent work focusing on neighborhood approaches for range estimation and operationalizing expert knowledge in species assessments.

• Spatial and Temporal Representation in Humanities
• Geospatial Data Modeling
• Digital Humanities
• +۷ مورد دیگر

Professor Leif Isaksen is a leading scholar in Digital Humanities and Ancient History at the University of Exeter, holding a chair in the Department of Classics, Ancient History, Religion and Theology. He also serves as Theme Lead for Humanities, Heritage and the Creative Industries at the Institute for Data Science and Artificial Intelligence (IDSAI). With a background in archaeology and a focus on Spatial-temporal representation in humanities Intelligent systems for historical data Digital skills development in arts and humanities , his work bridges classical scholarship and computational innovation. His research includes Pelagios Network projects like Recogito and Peripleo , which revolutionized semantic annotation and geospatial analysis of ancient texts. He directed the Cluny Hill Dig and co-founded initiatives like Hot Source! and DISKAH to democratize digital humanities skills. Key professional roles include: Executive Board Chair of ADHO (2019-2021) Co-Director of Web Science CDT at Southampton Active leadership in CAA, EADH, and ISHMap Scientific honors include fellowships at the Society of Antiquaries of Scotland and former affiliations with the Alan Turing Institute and Society of Antiquaries of London . His work aligns with UN Sustainable Development Goals 9: Industry, Innovation and Infrastructure and 4: Quality Education .

Ahmed Elbeltagiمشاهده پروفایل

استادیار

• Hydrology
• Agricultural Water Management
• Climate Change Adaptation
• +۶ مورد دیگر

Ahmed Elbeltagi is an Assistant Professor in the Agricultural Engineering Department at Mansoura University's Faculty of Agriculture. His work focuses on hydrology, agricultural water management, and climate change adaptation. Specializes in data-driven modeling for water resource optimization Integrates machine learning with traditional hydrological models Active in climate change impact assessments on agricultural systems Recent research trends include: Developing open-source tools like Aqua-MC for irrigation simulation Applying hybrid deep learning models for evaporation prediction Advancing water quality assessment through multivariate analysis Exploring economic applications of wetlands in arid regions He collaborates with institutions across Egypt, India, China, and Saudi Arabia, with a focus on sustainable water management solutions.

Mila N. Koevaمشاهده پروفایل

دانشیار

• Geospatial Technologies
• Digital Twinning
• 3D Urban Modeling
• +۶ مورد دیگر

Mila N. Koeva is a Vice Dean Research and senior Associate Professor at the University of Twente's Faculty of Geo-Information Science and Earth Observation (ITC), Department of Urban and Regional Planning and Geo-Information Management. Her research focuses on 3D modeling and Digital Twins for land management and urban planning, integrating geospatial technologies, UAV data, and AI/ML methods. PhD in architectural photogrammetry MSc in Engineering (Geodesy) Research Themes: Digital Twinning for urban ecosystems AI-driven cadastral boundary extraction 3D modeling with LiDAR and satellite data Global partnerships in Rwanda, Kenya, and Ethiopia Interoperability standards for local digital twins Scientific Contributions: Geospatial World Innovation Award 2021 Copernicus Masters Competition (3rd place 2016) Editorial roles in Photogrammetric Records and MDPI journals Keynote speaker at 3D GeoInfo, GI Forum, and FIG events Her educational impact includes developing courses, lecturing, and supervising students whose work has received top awards in The Netherlands and international competitions.

Ting Sunمشاهده پروفایل

دانشیار

• Urban climate modelling
• Climate change impacts and adaptation
• Extreme weather events in cities
• +۵ مورد دیگر

Dr Ting Sun is an Associate Professor in Climate & Meteorological Hazard Risks at University College London , Department of Risk and Disaster Reduction. He earned his BEng (2009) and PhD in Hydrology (2013) from Tsinghua University , followed by a visiting period at Princeton University (2011–2012). After postdoctoral appointments at Tsinghua and the University of Reading , he held a NERC Independent Research Fellowship at Reading (2017–2022) before joining UCL in May 2022. Education PhD in Hydrology, Tsinghua University, 2013 BEng in Hydraulic Engineering, Tsinghua University, 2009 Visiting PhD Student, Princeton University, 2011–2012 Research Interests Dr Sun’s work converges on urban climate modelling across scales —from neighbourhood blocks to global grids—focusing on the impacts of weather and climate extremes such as heat waves and extreme rainfall in cities. He is the lead developer of the Surface Urban Energy and Water balance Scheme (SUEWS) and its Python wrapper SuPy , developed in collaboration with Prof Sue Grimmond’s micromet group. He also contributes as a core member of the Urban Multi-scale Environmental Predictor (UMEP) development team. His multidisciplinary expertise integrates hydro-climate dynamics, computational modelling, machine learning, built-environment processes, and public-health linkages . Research Trends from Recent Publications Across the 15 most recent articles, a clear trajectory emerges from high-resolution urban-process modelling toward integrated socio-environmental assessments . Studies published in 2024–2025 couple atmospheric models (WRF-SUEWS) with global building-morphology datasets (GLAMOUR) to quantify how cities alter rainfall patterns, temperature sensitivity, and heat-related mortality. Earlier works progressively refined SUEWS’s physical parameterisations and Python accessibility, while recent outputs leverage deep-learning remote-sensing tools (SHAFTS) and hybrid hydrological-neural architectures to deliver actionable insights for urban planning and climate adaptation. Scientific Awards & Fellowships NERC Independent Research Fellowship , University of Reading, 2017–2022 HEA Fellowship , University College London, 2023 Professional Service & Editorial Roles Topic Editor , Geoscientific Model Development (from 2025) Editorial Board Member , Scientific Data (from 2024) Peer review and consultancy for journals, conferences, and policy bodies Supervision of taught-course projects and research degrees External examining and mentoring Labs, Teams & Collaborations Dr Sun leads and collaborates within the UCL Department of Risk and Disaster Reduction , working closely with the micromet group at the University of Reading (Prof Sue Grimmond) on SUEWS/SuPy development. He is an active member of the UMEP consortium and maintains extensive international collaborations spanning Tsinghua University, Princeton, and numerous European research centres, underpinning a vibrant, interdisciplinary research network focused on urban climate resilience.

Chaopeng Shenمشاهده پروفایل

استاد

• Hydrology
• Deep Learning
• Physics-Informed Machine Learning
• +۹ مورد دیگر

Chaopeng Shen is a Professor in the Department of Civil and Environmental Engineering at Pennsylvania State University. His research bridges hydrology with state-of-the-art deep learning and differentiable modeling techniques, focusing on advancing our understanding of hydrologic cycles and their interactions with ecosystems, energy, and carbon cycles. He leads the Multi-scale Hydrology, Processes and Intelligence group (MHPI) and has developed the Process-based Adaptive Watershed Simulator (PAWS) for large-scale hydrologic modeling. Shen's work emphasizes physics-informed machine learning , where deep learning components are integrated with process-based equations through differentiable modeling. This approach enables training neural networks using big data while respecting physical laws, leading to improved generalizability and robustness. His group has demonstrated advantages of differentiable models in rainfall-runoff prediction, routing, ecosystem modeling, and water quality studies. Notably, his team's deepLDB project addresses landslide prediction using AI and big datasets. Recent publications highlight his contributions to global water modeling (grid-LSTM, differentiable Muskingum-Cunge routing), extreme flood forecasting (probabilistic diffusion models), and hydrologic uncertainty quantification . Shen actively engages in interdisciplinary collaborations through the PRISM Cooperative Institute, which aims to integrate multi-domain data for systemic risk assessment. His group has advised students including Dapeng Feng, Wen-Ping Tsai, Kuai Fang, Xinye Ji, and Tasnuva Mahjabin. Shen's research is supported by the National Science Foundation (NSF), Department of Energy (DoE), USGS, Google.org, and the Gates Foundation. He serves as Editor for the Journal of Geophysical Research - Machine Learning & Computation and Chief Editor for Frontiers in Water: Water & AI. His open-source software tools like PAWS and deepLDB are available through dedicated project websites.

Patrick Parkمشاهده پروفایل

استادیار

• Social Network Analysis
• Computational Sociology
• Open Source Software Research
• +۵ مورد دیگر

Dr. Patrick Park is an Assistant Professor at the Software and Societal Systems Department within Carnegie Mellon University's School of Computer Science. His work bridges computational and social sciences to analyze network dynamics, digital communication, and open source systems. Current position: Assistant Professor Institution: Carnegie Mellon University Department: Software and Societal Systems Park's research focuses on social network analysis, behavioral modeling, and computational sociology. Key contributions include studies on network diversity, geospatial visualization techniques, and digital communication patterns across civilizations. His recent publications (2023-2024) highlight expertise in network visualization, social contagion, and open source innovation. Earlier work spans topics like organizational classification, user behavior paradoxes, and cross-cultural communication networks.

• Geophysics
• Remote Sensing
• Computer Vision
• +۲ مورد دیگر

Scott Staniewicz is a researcher at the University of Texas at Austin in the Department of Aerospace Engineering and Engineering Mechanics. His work focuses on geophysical applications of computer vision and remote sensing, particularly using Interferometric Synthetic Aperture Radar (InSAR) to detect surface deformation and tropospheric noise features. Academic Affiliation: University of Texas at Austin Research Focus: Surface deformation analysis, InSAR data processing, tropospheric noise mitigation Email: scott.stanie@utexas.edu Staniewicz's research employs computer vision techniques like Laplacian of Gaussian (LoG) filtering to identify spatially coherent deformation features (e.g., subsidence/uplift in oil-producing regions). His methods integrate noise spectrum estimation from real data and simulations to distinguish true deformation signals from atmospheric artifacts. Recent work includes software development for automated InSAR analysis and large-scale studies of anthropogenic deformation in the Permian Basin. He has contributed to open-source tools such as Blobsar (2025a) and Troposim (2025b) for deformation detection, and collaborated on studies analyzing seismic sequences (Skoumal et al., 2020), tropospheric delay corrections (Li et al., 2019; Yang et al., 2024), and statewide seismic networks (Savvaidis et al., 2019). His publications demonstrate expertise in combining computer vision with geophysical data analysis.

Matthias Stürmerمشاهده پروفایل

استاد

• Digital Sustainability
• Artificial Intelligence
• Natural Language Processing (NLP)
• +۴ مورد دیگر

Matthias Stürmer is a Professor at Bern University of Applied Sciences (BFH) and Head of the Institute for Public Sector Transformation (90%) while also serving as Head of the Digital Sustainability Research Center at the University of Bern's Institute of Computer Science (10%). His roles include teaching, research, and consulting on digitalization topics such as digital sustainability, open source software, AI, NLP, open data, and public procurement. He earned a Dr. sc. ETH Zurich in 2009 and habilitation in 2020. His career includes senior roles at EY and Liip AG, and he holds leadership positions in organizations like CH Open and the Parliamentary Group for Digital Sustainability. **Education**: PhD (ETH Zurich, 2009), Licentiate in Business Administration (University of Bern, 2005). Studies included computer science and business administration, with an Erasmus semester at the University of Oviedo (Spain). **Research Interests**: Focus on digital sustainability, digital sovereignty, AI ethics, open source governance, smart cities, and public procurement strategies. His work bridges technical innovation with public sector challenges, emphasizing long-term societal benefits over short-term vendor dependencies. **Publications**: Over 38 peer-reviewed articles and book chapters, including foundational work on digital sustainability frameworks, open government data impact analysis, and collaborative innovation models. Recent focus areas include data colonialism risks and sustainable environmental data management. **Awards**: While no explicit awards listed, his leadership roles and prolific publications highlight recognition in academic and policy circles. **Advising & Grants**: Advises on public sector digitalization policies, contributes to Swiss federal IT strategies, and leads research projects funded by organizations like the University of Bern. Active in shaping Open Source adoption policies for public institutions. **Labs/Teams**: Directs the Research Center for Digital Sustainability at the University of Bern, collaborating with industry and government partners on projects like the Open Data Impact Framework and Open Finance initiatives.

• Water resources engineering
• Surface water hydrology
• Data science
• +۷ مورد دیگر

Jeff Sadler is an Assistant Professor in the Department of Biosystems & Agricultural Engineering at Oklahoma State University, where he also serves as an Extension Specialist for Water Resources with OSU Extension. He leads the WaDE (Water Data and Education) Lab, focusing on data science and machine learning applications in water resources. Education: PhD in Civil and Environmental Engineering, University of Virginia (2019) MS in Civil Engineering, Brigham Young University (2015) BS in Civil Engineering, Brigham Young University (2013) Research Interests: Jeff’s research lies at the intersection of data science and water resources. He specializes in machine learning, particularly physics-guided and process-aware deep learning, for modeling stream temperature, water quality, flood dynamics, and hydrological forecasting. His work emphasizes real-time decision support, reproducible modeling, and integrating domain knowledge into data-driven systems. Recent Research Trends: His recent publications demonstrate a strong focus on advanced deep learning architectures (e.g., graph neural networks, recurrent models), data assimilation, multi-task learning, and surrogate modeling for environmental systems. Applications center on the Delaware River Basin and coastal Virginia, with implications for climate change adaptation and infrastructure resilience. Scientific Awards: No awards explicitly listed in the provided text. Advising and Grants: Jeff mentors graduate students and supervises master's and doctoral research. He is actively funded through multiple grants from the USDA, NOAA, and USGS, supporting projects in water quality monitoring, rural health, evapotranspiration forecasting, and integrated hydrological modeling. Labs and Teams: He leads the WaDE Lab, which develops data-driven tools for water resource education and management. He has collaborated extensively with researchers from the U.S. Geological Survey, University of Virginia, and other institutions on cyberinfrastructure, reproducible modeling, and environmental machine learning.

Stephen Brooksمشاهده پروفایل

استاد

• Computer Graphics
• Visualization
• Human-Computer Interaction
• +۱۳ مورد دیگر

Stephen Brooks is a Professor in the Faculty of Computer Science at Dalhousie University, actively contributing to research and education in computer graphics, visualization, and human-computer interaction. He is affiliated with the Human-Computer Interaction, Visualization & Graphics research cluster and currently supervises multiple graduate students on diverse projects. PhD in Computer Science, University of Cambridge (2004) MSc in Computer Science, University of British Columbia (2000) BSc, Brock University (1998) His research focuses on computer graphics and visualization, particularly non-photorealistic rendering, image editing, 3D geospatial systems, ocean visualization, and real-time rendering of natural phenomena. He has also worked in sound synthesis and motion editing. His recent publications show a strong emphasis on visual analytics, network flow visualization, and ocean science applications. His work spans interdisciplinary domains including environmental science, genomics, cybersecurity, and digital art. He has developed visualization tools for ocean science under a major CFREF-funded initiative and created novel methods for rendering stained glass, mixed media art, rivers, and ocean surfaces. His research integrates perception, automation, and user interaction to enhance visual analysis. Notable scientific contributions include work on tone mapping optimization, uncertainty visualization using chromatic aberration, semantic object clouds, and hybrid 2D/3D GIS. His publications appear in top venues such as IEEE TVCG, ACM Transactions, and SIGGRAPH. NSERC Discovery Grants Canada First Research Excellence Fund (CFREF) NSERC CREATE Mitacs Accelerate and Globalink CFI New Opportunities Grant Cyber Security Research and Development Grant He has supervised numerous PhD, Master’s, and undergraduate students in areas including ocean visualization, tone mapping, network security, VR, and geospatial analytics. He teaches courses in Game Design, Visualization, Computer Animation, and Network Computing, emphasizing project-based and interdisciplinary learning. He leads research in visual analytics for network data (FloVis), ocean science, and mixed reality collaboration. His lab develops interactive systems for data exploration in domains ranging from marine biology to cybersecurity. Future work includes expanding ocean-first climate visualization and enhancing mixed presence collaboration in immersive environments.

• Sustainable transport planning
• Urban spatial modeling
• GIS applications in planning
• +۳ مورد دیگر

Professor Yngve Karl Frøyen works at the Department of Architecture and Planning, Faculty of Architecture and Design, Norwegian University of Science and Technology (NTNU). With expertise in sustainable transport solutions, urban spatial modeling, and GIS applications for planning, he has taught and supervised urban and regional planning topics since 2010. His work spans multiple master programs and involves improving transport modeling tools for walking, transit, and bicycling modes. Research Focus: Sustainable urban transport (walking, bicycling, public transit), urban density, GIS methods, land use-transport interactions, and urban logistics. Teaching: Courses in GIS methods, land use-transport integration, regional planning, and master thesis supervision. Publications: 15+ works on transport modeling, urban density impacts, bicycle infrastructure, and planning methodology. Outreach: Regularly presents at conferences and seminars on topics like urban logistics, walking modeling, and transport policy. His academic career spans from 1981 civil engineer graduation to current professorship, with prior roles at Norwegian Institute of Urban and Regional Research (NIBR) and SINTEF. He combines technical GIS proficiency with policy-oriented planning expertise.

Anand Padmanabhanمشاهده پروفایل

عضو هیئت علمی

• Advanced Cyberinfrastructure
• CyberGIS
• Geospatial Data Science
• +۵ مورد دیگر

Anand Padmanabhan is a Research Associate Professor in the Department of Geography & Geographic Information Science at the University of Illinois at Urbana-Champaign (UIUC), affiliated with the School of Earth, Society & Environment within the College of Liberal Arts & Sciences. He holds a Ph.D. in Computer Science from the University of Iowa, alongside an MS in Computer Science (University of Iowa) and a BE in Computer Engineering (University of Mumbai). His research focuses on advanced cyberinfrastructure, cyberGIS, geospatial data science, and high-performance computing. He leads the spatial algorithms and systems team at the CyberGIS Center for Advanced Digital and Spatial Studies, developing cyberGIS capabilities to leverage advanced computing for geospatial innovation. His work emphasizes scalable geocomputation, cloud-based frameworks, and reproducible research environments, with contributions to tools like CyberGIS-Compute and EasyScienceGateway. Recent publications highlight advancements in science gateway frameworks, middleware systems, and geospatial education platforms. He serves as Online MS Program Adviser and has secured NSF and EPA grants for interdisciplinary projects. His work spans transdisciplinary training programs, urban sensing analytics, and integration of social media with geospatial data.