جستجوی استاد راهنمای دانشگاهی

• Computer Vision
• Neural Networks
• Pattern Recognition
• +۳ مورد دیگر

Nikolaos Vassilas serves as Professor in the Department of Informatics and Computer Engineering at the University of West Attica, Greece, with leadership roles including Director of the Intelligent Knowledge, Image & Information Systems research Laboratory (ISLab) since 2019 and former Director of the Joint Greek-French Master Degree Program (2016-2020). His academic journey includes research positions at NCSR "Demokritos" and EPFL. His educational credentials feature a Diploma in Electrical Engineering from Aristotle University of Thessaloniki (1983), and M.S.E.E. and Ph.D. degrees from the University of Minnesota (1987, 1990). Professional affiliations include IEEE Computational Intelligence Society, Hellenic Society of Artificial Intelligence, and Greek Computer Society. Professor Vassilas' research centers on Computer Vision and Neural Networks with applications in urban analysis and remote sensing. His work integrates deep learning for building extraction from aerial/LiDAR data, semantic modeling in 3D urban environments, and neural network-based environmental prediction systems. Key methodological focuses include mean-shift algorithms, Hough transforms, and multisource spatial data fusion. Analysis of his recent publications reveals consistent specialization in computer vision techniques for urban infrastructure analysis, particularly building contour detection and 3D reconstruction using convolutional neural networks. The integration of aerial imagery with elevation data and robust line detection algorithms represents a dominant research trajectory across his 70+ publications. No scientific awards were documented in the source materials. He has coordinated two European Union co-funded research programs and participated in multiple national projects, with expertise in environmental data processing and intelligent spatial analysis systems. His leadership extends to directing research laboratories and international academic programs, demonstrating significant grant management experience. Professor Vassilas leads the Intelligent Knowledge, Image & Information Systems research Laboratory (ISLab), which focuses on advancing computer vision techniques for urban planning and environmental monitoring applications through interdisciplinary team collaboration.

Demetrios Eliadesمشاهده پروفایل

استادیار

• Smart Water Networks
• Water Quality Monitoring
• Cyber-Physical Security
• +۲ مورد دیگر

Demetrios Eliades is a Research Assistant Professor at the KIOS Research and Innovation Center of Excellence at the University of Cyprus. He holds a Diploma in Electrical and Computer Engineering from Aristotle University of Thessaloniki, an MSc in Artificial Intelligence from the University of Edinburgh, and a PhD in Electrical Engineering from the University of Cyprus. His research focuses on Smart Water Networks, including water loss reduction, quality assurance, contamination response, and cyber-physical security. He develops open-source tools like the EPANET-MATLAB Toolkit and coordinates projects such as the Battle of the Leakage Detection and Isolation Methods (BattLeDIM) competition. His cross-disciplinary work extends to power systems, robotics, and archaeometry. Dr. Eliades has coordinated multiple European projects including Interreg SmartWater2020 and H2020 PathoCERT, and contributed to COVID-19 response through a national information management platform. His publications emphasize AI integration in water systems, contamination management, and infrastructure resilience.

Kim Carlsonمشاهده پروفایل

دانشیار

• Environmental Science
• Sustainability Certification
• Tropical Deforestation
• +۵ مورد دیگر

Kim Carlson is an Associate Professor of Environmental Studies at New York University. Her research focuses on the intersection of environmental science and policy, particularly in tropical regions. She investigates the impacts of agricultural sustainability certification (e.g., palm oil) on deforestation, community well-being, and labor practices in Indonesia. Her work integrates geospatial data analysis, field surveys, and interviews to understand complex land-use dynamics. She emphasizes interdisciplinary approaches, advocating for programs that bridge natural and social environmental sciences. Her current projects examine how certification systems like the Roundtable on Sustainable Palm Oil (RSPO) affect environmental and social outcomes in oil palm plantations. She collaborates with Indonesian researchers to assess policy effectiveness and smallholder inclusion. Carlson highlights the importance of mentorship for students, encouraging them to engage with professors for career guidance and networking. Her research spans topics such as carbon sequestration, zero-deforestation supply chains, and the environmental impacts of commodity crops. While no awards are listed, her contributions to environmental policy and tropical conservation are evident through her extensive publication record. She advises students on academic and professional pathways but no specific advisees are named in the provided text.

James Allanمشاهده پروفایل

استاد

• Information Retrieval
• Interactive Information Retrieval
• Cross-lingual Information Retrieval
• +۵ مورد دیگر

James Allan is a Distinguished Professor and Associate Dean of Research & Engagement in the Manning College of Information and Computer Sciences at the University of Massachusetts Amherst. He joined the Computer Science Department in 1994 and has been a Professor since 2008. He also directs the Center for Intelligent Information Retrieval (CIIR) and holds a part-time joint appointment as a GI-CoRE Affiliated Professor with the Faculty of Information Science and Technology at Hokkaido University, Japan. Dr. Allan received his PhD and MS in Computer Science from Cornell University in 1995 and 1991, respectively, and an AB in Mathematics from Grinnell College in 1983. Prior to his academic career, he spent five years as a systems programmer/analyst at Dickinson College and co-founded a startup selling email software in the 1980s. Professor Allan's research focuses on information retrieval, with particular emphasis on interactive information retrieval systems, automatic information organization, and evaluation methodologies. His work explores how novelty can be incorporated into retrieval algorithms, techniques for querying across languages, and methods for recognizing controversial or misleading information in text on the internet. His recent work has expanded into understanding large language models for information retrieval tasks, including mechanistic analysis of ranking LLMs and explainability in search results. His research has significant implications for improving user experience in search systems and addressing challenges in misinformation detection. Dr. Allan has received numerous prestigious awards, including Best Paper awards at SIGIR in 2001 and 2006, a Best Student Paper from CHIIR in 2017, and Best application paper from ECIR in 2019. He received the SIGIR Test of Time Award for a 1998 paper on event detection and tracking and the ECIR Test of Time Award for a 2009 paper on topic models in IR. In 2021, he was elected to the SIGIR Academy and elevated to Fellow of the ACM. He has served on the CRA Board of Directors since 2018, including as Treasurer. As Associate Editor of ACM's Transactions on Information Systems (TOIS) and Elsevier's Information Processing and Management (IPM), and as a member of the editorial board of Foundation and Trends in Information Retrieval, Dr. Allan has significantly shaped the field. He has served on organizing and program committees for major conferences including SIGIR, CIKM, and WSDM, and chaired the SIGIR organization. His leadership extends to directing the CIIR, which has been instrumental in shaping the International Conference on the Theory of Information Retrieval (ICTIR). The Center for Intelligent Information Retrieval (CIIR), which Dr. Allan directs, is a leading research center focused on advancing information retrieval technologies. The center has been at the forefront of research in interactive information retrieval, cross-lingual information retrieval, and novel evaluation methodologies. Under his leadership, CIIR researchers have made significant contributions to understanding user behavior in search systems and developing more effective and transparent retrieval algorithms.

Shabbar I. Ranapurwalaمشاهده پروفایل

دانشیار

• Opioid Disorders and Overdose Prevention
• Firearm Violence Prevention
• Suicide Surveillance and Prevention
• +۶ مورد دیگر

Shabbar I. Ranapurwala is an Associate Professor in the Department of Epidemiology at the UNC Gillings School of Global Public Health. He also serves as Adjunct Assistant Professor at the University of Iowa Department of Epidemiology and Assistant Director for Research Methods at the UNC Injury Prevention Research Center (IPRC). His work focuses on preventing opioid disorders, overdose deaths, firearm violence, and gender-based violence while addressing racial inequities in public health outcomes. He employs advanced analytics, causal inference, and quasi-experimental methods on large datasets to evaluate policy impacts at state and local levels. Education: PhD in Epidemiology (UNC-Chapel Hill, 2014), MPH in Environmental Health (Western Kentucky University, 2009), BHMS in Homeopathic Medicine (Maharashtra University of Health Sciences, India, 2004). Research interests include opioid policy evaluation, suicide surveillance (via NIH-funded INSPIRE study), domestic violence protective orders (NIJ-funded eProtect), and firearm violence reduction. He co-leads the Anti-racism Interest Group at SAVIR and contributes to North Carolina's Opioid and Prescription Drug Abuse Advisory Council. Key achievements include methodological contributions to violence prevention epidemiology and publications in Am J Public Health , Inj Prev , and PloS ONE . His NIH- and CDC-funded grants address opioid use disorder algorithms, justice-involved populations, and suicide prevention. Labs/Teams: Active member of UNC IPRC collaborating with North Carolina's Division of Public Health. Teaches EPID 690: Intervention Epidemiology.

• Semantic Web
• Linked Data
• Ontology Engineering
• +۷ مورد دیگر

Dr. Stefan Schlobach is an Associate Professor at the Faculty of Science, Vrije Universiteit Amsterdam, affiliated with the Artificial Intelligence department, Network Institute, and Knowledge Representation and Reasoning group. His research focuses on Semantic Web, Linked Data, Ontology Engineering, and Hybrid Intelligence systems. He has published over 116 peer-reviewed works and supervised 6 PhD theses. Recent projects include robotic knowledge acquisition (ORKA ontology), explainable AI for security systems, and knowledge engineering for virtual heritage applications. He co-developed the LOTUS search framework for big linked data and contributed to the CoPla ontology for agriculture. His work bridges theoretical foundations (e.g., argumentation systems) with applied domains (e.g., cyber-physical systems, cultural heritage digitization). Research Interests: Semantic Web Technologies Knowledge Graphs & Ontology Engineering Hybrid Intelligence (Human-AI Collaboration) Robotic Perception Systems Explainable AI Entity Linking & Identity Resolution Key Contributions: Developed LOTUS adaptive search system (2016 prize-winning work) Created ORKA ontology for robotics knowledge acquisition Pioneered perceived-entity linking methodologies Advocated knowledge engineering principles for hybrid systems Teaching: Leads courses in Artificial Intelligence, Knowledge Representation, and Semantic Technologies at both undergraduate and graduate levels.

• Metabolic Dysfunction-Associated Liver Disease
• Non-Alcoholic Fatty Liver Disease
• Liver Disease Diagnostics
• +۳ مورد دیگر

Stergios Kechagias is a Professor of Internal Medicine at Linköping University, affiliated with the Department of Health, Medicine and Caring Sciences (HMV) and the Division of Diagnostics and Specialist Medicine (DISP). He holds a medical degree (1996) and a PhD (2001), and became a Professor in 2013. His research focuses on metabolic dysfunction-associated steatotic liver disease (MASLD), non-alcoholic fatty liver disease (NAFLD), and innovative diagnostic methods using MRI and biomarkers. Key research interests include fibrosis progression, vascular biomarkers, and dietary influences in liver diseases. Collaborative projects, such as the Swedish initiative for Primary Sclerosing Cholangitis (SUPRIM), emphasize longitudinal studies and national healthcare partnerships. Notable achievements include developing non-invasive liver diagnostics and advancing understanding of MASLD epidemiology and clinical outcomes. He has received awards like the 2017 Pedagogue of the Year and the 2022 Bergdahl Award. His work integrates clinical practice with academic research, addressing global health challenges in liver disease management. Teaching contributions include the Medical Program at Linköping University.

Richard Knippersمشاهده پروفایل

مدرس

• Geo-information Technology
• Geographical Information Systems (GIS)
• Spatial Referencing
• +۳ مورد دیگر

Dr. Richard Knippers is a Lecturer in the Department of Geo-information Processing at the University of Twente's Faculty of Geo-Information Science and Earth Observation (ITC). He has been affiliated with ITC since 1990, contributing to education, research, and consulting across multiple continents. His expertise spans geo-information technology management, GIS applications, cartography, and spatial referencing systems. Education: Studied human geography with cartography at Utrecht University. Professional roles include Director of Studies for the Diploma Course in Geo-informatics (GFM.4). Research focuses on GIScience fundamentals, spatial data management, and international capacity-building projects in countries like the Netherlands, France, Colombia, Argentina, Bolivia, Egypt, and Namibia. His work bridges theoretical GIS concepts with practical applications through educational materials and collaborative initiatives. Publications emphasize foundational GIS principles, spatial data frameworks, and educational resources. Notable outputs include the 'Core of GIScience' textbook chapters and Mongolian-language GIS textbooks.

Ahmad Jradeمشاهده پروفایل

دانشیار

• Construction Engineering and Management
• Sustainable Building Design
• Building Information Modeling (BIM)
• +۷ مورد دیگر

Dr. Ahmad Jrade is an Associate Professor in the Department of Civil Engineering at the University of Ottawa, serving as the Graduate Program Coordinator and Director of the Ottawa Centre for Innovative Construction Engineering (OCICE). He holds a Ph.D. from Concordia University, an M.A.Sc. from Concordia, and a B.A.Sc. from Beirut Arab University. His research focuses on integrating Building Information Modeling (BIM), Life Cycle Cost Analysis (LCCA), Virtual Reality (VR), and Circular Economy principles to enhance sustainable construction practices, particularly in universal design and infrastructure projects. He has extensive experience in construction cost optimization, sustainable building design, and accessibility engineering. Before joining the University of Ottawa, he was an Assistant Professor at Western Michigan University, coordinating their Construction Engineering program. His work emphasizes BIM integration with sustainability metrics, energy analysis tools, and universal design standards to improve decision-making at the conceptual design stage. He has pioneered models for waste management in construction/deconstruction, bridge design optimization, and age-in-place housing solutions. His contributions include developing cloud-based BIM-VR systems, GIS-BIM site planning tools (ArcSPAT), and frameworks for evaluating accessibility in infrastructure projects. Dr. Jrade also leads research in corrosion effects on reinforced concrete structures and disaster-resistant construction methods. Key areas of innovation include Construction 4.0 technologies, circular economy applications in construction, and bridging the gap between BIM and environmental assessments. His interdisciplinary approach addresses both technical and societal challenges in creating sustainable, accessible, and cost-effective built environments.

Neil Floodمشاهده پروفایل

پژوهشگر ارشد

• Remote Sensing
• Environmental Science
• Satellite Imagery Analysis
• +۳ مورد دیگر

Dr. Neil Flood is an Honorary Senior Fellow at the University of Queensland's School of the Environment. His research focuses on remote sensing techniques, satellite imagery analysis, and environmental monitoring. He specializes in applying multispectral data from sensors like Sentinel-2, Landsat, and SPOT to study vegetation dynamics, climate impacts, and land cover changes in Australia. His work often involves developing algorithms for automated classification and integrating machine learning (e.g., U-net CNN) into ecological studies. Dr. Flood collaborates on projects such as the Joint Remote Sensing Research Program and has contributed to studies on BRDF effects, surface reflectance continuity, and rangeland management. His publications highlight advancements in satellite data processing, including comparisons between sensor systems and applications in environmental modeling. He has also authored reports on vegetation cover synthesis and fire ecology in grazing lands. Despite no listed students or awards, his contributions to open-source tools (e.g., GEOBIA systems) underscore his commitment to advancing remote sensing methodologies.

• Remote Sensing
• Forest Ecology
• Climate Change
• +۳ مورد دیگر

Harry Owen is a Postdoctoral Research Associate at the Department of Geography, University of Cambridge , working with Dr. Emily Lines. His research focuses on remote sensing and forest ecology , with an emphasis on 3D data analysis using techniques like terrestrial laser scanning (TLS) and UAV imagery. He holds an MSc in Environmental Monitoring from King's College London and a BSc in Geography from the University of Plymouth. His work explores forest-landscape dynamics , tree species classification, and the impacts of climate change on forest structure. He has contributed to benchmarking datasets like FOR-species20K and developed frameworks for canopy segmentation using deep learning. Key methodologies include integrating TLS and satellite data to assess vegetation health, biodiversity, and ecosystem vulnerability. Notable projects include studying ash dieback detection via UAV-derived metrics and reimagining forest ecology through 3D remote sensing. His research bridges ecological theory with applied conservation, emphasizing scalable solutions for monitoring global forests. Collaborations with institutions like the Institute of Zoology highlight his interdisciplinary approach to environmental challenges.

Charles Campمشاهده پروفایل

استاد

• Structural Optimization
• Computational Mechanics
• Seismic Design
• +۳ مورد دیگر

Dr. Charles Camp is a Professor of Civil Engineering at the University of Memphis, specializing in Structural Optimization and Computational Mechanics. He holds a Ph.D. in Civil Engineering from Oklahoma State University (1987), an M.S. from Auburn University (1986), and a B.S.C.E. from Auburn University (1981). His research focuses on advanced optimization techniques, machine learning applications in structural analysis, and seismic design methodologies. Teaching responsibilities include courses such as CIVL 1101 (Civil Engineering Measurements), CIVL 1112 (Civil Engineering Analysis), and graduate-level courses like CIVL 7111 (Computational Mechanics) and CIVL 7117 (Finite Elements in Structural Mechanics). His research spans structural health monitoring using CNNs, optimization of retaining walls, and probabilistic seismic loss analysis. Recent publications emphasize machine learning for defect detection in wooden structures and the application of swarm intelligence algorithms. His work bridges computational methods with practical civil engineering challenges, addressing sustainability and resilience in infrastructure systems. Dr. Camp has contributed to over 100 publications, including book chapters and edited volumes, and has collaborated on projects such as seismic instrumentation of bridges and GIS integration in engineering education. His research often explores innovative computational frameworks to enhance structural design efficiency and safety.

Jun Zhuمشاهده پروفایل

استاد

• Spatial statistics
• Spatio-temporal statistics
• Markov random fields
• +۷ مورد دیگر

Jun Zhu is a Professor of Statistics at the University of Wisconsin-Madison, affiliated with the Department of Statistics and cross-listed in the Department of Entomology, Department of Biostatistics and Medical Informatics, and the Center for Demography and Ecology. His research focuses on spatial and spatio-temporal statistical methodologies, applied to ecological, environmental, agricultural, and health systems. He holds prestigious awards including the Distinguished Achievement Medal from the American Statistical Association and election to the International Statistical Institute. Education: PhD in Statistics (Iowa State University, 2000), MSE in Mathematical Sciences (Johns Hopkins University, 1995), BA in Mathematics and Computer Science (Knox College, 1994). Research emphasizes methodological development for spatial data analysis, with applications in agriculture, ecology, and public health. Key contributions include cluster detection algorithms, spatial regression models, and spatio-temporal analyses of environmental and demographic phenomena. His work bridges theoretical statistics with interdisciplinary collaborations, addressing real-world challenges such as disease mapping and climate change impacts. Scientific Awards: Distinguished Achievement Medal (ASA) Elected Member (International Statistical Institute) Fellow (American Statistical Association) Presidential Award (American Society of Agronomy) Teaching and advising: Leads courses on spatial statistics, time series analysis, and statistical consulting. Advises on methodological and collaborative projects at the intersection of statistics and environmental science. Labs/Teams: Active in interdisciplinary research teams focused on spatial demography, ecological modeling, and statistical ecology.

• Environmental Engineering
• Biogeochemistry
• Ecohydrology
• +۷ مورد دیگر

Professor Federico Maggi is a Professor in Environmental Engineering at the University of Sydney's School of Civil Engineering, leading the Environmental Engineering Laboratory. He also serves as a Guest Faculty Affiliate at the Lawrence Berkeley National Laboratory. His academic journey includes a ME from the Polytechnic of Turin (1999) and a PhD from Delft University of Technology (2005), followed by postdoctoral roles at Duke University and UC Berkeley. His research focuses on geophysical flows, biogeochemical cycles, pesticide pollution, and sustainable agriculture. Notable projects include the BRTSim computational solver for environmental systems and the PEST-CHEMGRIDS global pesticide mapping initiative. Awards include the 2024 Australian Nation Champion of the Frontier Planet Prize and multiple grants from the University of Sydney and international bodies. Maggi teaches courses in hydrology and water resources engineering, and advises students on topics like soil carbon dynamics and biogeochemical modeling. His lab develops advanced models for nutrient cycling, sediment transport, and climate change impacts.

• GeoSocial Analysis
• Digital Image Analysis
• Remote Sensing
• +۶ مورد دیگر

Anthony Stefanidis is a Professor of Computer Science at the College of William & Mary. He holds a Dipl. Eng. from the National Technical University of Athens, Greece, and M.S. and Ph.D. from The Ohio State University. His research focuses on GeoSocial Analysis and Digital Image Analysis, leveraging social media and remote sensing data to address challenges in urban planning, crisis management, and public health. Before joining William & Mary in 2020, he held tenured positions at George Mason University (2007–2020) and the University of Maine (1996–2006), along with a postdoctoral stint at ETH Zurich (1993–1995). His research has been funded by agencies such as DHS, NGA, IARPA, NSF, and the European Union. Key themes in his work include: Extracting intelligence from social media for societal and environmental insights Developing geospatial analytics for slum detection, disaster response, and urban morphology Analyzing bot behavior and misinformation in online networks Over 100 peer-reviewed publications and three edited books reflect his interdisciplinary contributions. Recent work emphasizes fusion of satellite and social data to model human behavior, migration, and educational outcomes in underserved regions.