جست‌وجوی استاد و پژوهشگر

K. Selçuk Candanمشاهده پروفایل

استاد

• Data Science
• Database Systems
• Machine Learning
• +۵ مورد دیگر

K. Selçuk Candan is a Professor of Computer Science and Engineering at Arizona State University (ASU) and the Director of the Center for Assured and Scalable Data Engineering (CASCADE). He holds affiliations with the Global Institute of Sustainability and the Center for Cybersecurity and Digital Forensics. His academic roles include interim co-director of the School of Computing and Augmented Intelligence (2022) and coordinator of the Big Data Systems concentration. He earned his Ph.D. from the University of Maryland and his B.S. from Bilkent University. Education: Ph.D. Computer Science (University of Maryland, 1997), B.S. Computer Engineering (Bilkent University, 1993) Affiliations: CASCADE Director, Global Futures Scientist, NSF APPEX Center His research focuses on data management, analysis of heterogeneous data, and applications in healthcare, energy, and cybersecurity. He has authored over 250 peer-reviewed publications and secured $34M in grants. Key projects include pandemic modeling, building energy optimization, and cybersecurity for smart infrastructure. Recipient of the 2023 Daniel Jankowski Legacy Award and ACM SIGMOD Contributions Award, he emphasizes interdisciplinary collaboration and mentorship. He has advised 16 doctoral students and 35+ graduate students, contributing to teaching excellence awards. His work bridges academia and industry, with grants from NSF, DOE, and DoD. Current efforts include causal learning frameworks, spatio-temporal modeling, and cyber-infrastructure for pandemic response.

K. Selcuk Candanمشاهده پروفایل

استاد

• Data Management
• Multimedia Databases
• Distributed Systems
• +۵ مورد دیگر

K. Selcuk Candan is a Professor of Computer Science and Engineering at Arizona State University (ASU) and Director of the Center for Assured and Scalable Data Engineering (CASCADE). He holds affiliations with multiple institutes, including the Global Futures Scientists and Scholars and the Center for Cybersecurity and Trusted Foundations. Candan has been at ASU since 1997, following his PhD from the University of Maryland. His research focuses on managing and analyzing non-traditional data types like multimedia, web, and scientific data. Key interests include scalable data processing, sensor data integration, and accessibility technologies for visually impaired individuals. He has led numerous grants from NSF, DoD, and others, resulting in over 250 peer-reviewed publications and 9 patents. Notable contributions include the DataStorm framework for coupled simulations and the OASIS system for accessible digital content. Candan has served as program chair for top conferences like SIGMOD and MM, and is an ACM Distinguished Scientist. His awards include the SIGMOD Contributions Award and Dan Jankowski Legacy Award. He has advised numerous students and led interdisciplinary projects in areas like pandemic modeling (APPEX Center) and building automation security. His work bridges theory and application, emphasizing real-world impact in healthcare, urban systems, and educational accessibility.

Dylan Keonمشاهده پروفایل

استادیار

• Spatial Analysis
• Spatio-Temporal Data
• Climate Data
• +۵ مورد دیگر

Dylan Keon is an Assistant Professor (Senior Research) at Oregon State University's School of Electrical Engineering and Computer Science. He serves as the Associate Director of the Northwest Alliance for Computational Science & Engineering (NACSE). His research focuses on spatial analysis, spatio-temporal data systems, climate data production, and decision support systems for environmental and disaster management applications. He holds a Ph.D. in Computational Geography and M.S. in Plant Ecology and GIS/Statistics from Oregon State University, along with a B.S. in Botany from Western Michigan University. Dr. Keon has over 20 years of experience in developing geospatial tools for environmental monitoring, including projects funded by USDA, NSF, and other agencies. His work spans topics such as precision agriculture, climate modeling, tsunami engineering, and aquatic pathogen tracking. He currently leads operations on multiple USDA-funded initiatives and has contributed to critical infrastructure resilience frameworks for coastal regions. His research trends emphasize interdisciplinary collaboration, leveraging computational methods to address complex environmental challenges. Recent efforts include advancing solar radiation models, improving tsunami inundation simulations, and creating databases for tracking aquatic pathogens. Keon’s contributions bridge academic research with real-world applications, particularly in disaster preparedness and sustainable environmental practices.

Simon Creerمشاهده پروفایل

استاد

• Molecular Ecology
• Environmental DNA (eDNA)
• Biodiversity
• +۶ مورد دیگر

Simon Creer is a Professor of Molecular Ecology at Bangor University's School of Environmental & Natural Sciences, leading the Molecular Ecology and Evolution research group. His work focuses on biodiversity, ecological function, and evolutionary processes using molecular tools like environmental DNA (eDNA). He holds editorial roles in journals such as Molecular Ecology and Environmental DNA . Research Interests: Creer investigates biodiversity and ecosystem dynamics across terrestrial, aquatic, and aerobiological environments. Key areas include microbiome analysis, climate change impacts, and the application of eDNA for biomonitoring. His projects explore host-microbe interactions, circadian rhythms, and the ecological significance of genetic diversity in species ranging from amphibians to marine organisms. Grants & Projects: He leads the SUPERB project on forest restoration and contributes to studies on salmon immune health and amphibian disease resistance. Recent funding includes BBSRC and NERC grants. Publications: Over 130 peer-reviewed articles, including high-impact studies on eDNA applications, microbiome dynamics, and evolutionary genomics. Recent work highlights the role of photoperiod in aquaculture immunity and amphibian skin microbiome interactions. Awards: Fellow of the Royal Society of Biology (2016–2018).

• Internet of Things (IoT)
• Sensor Networks
• Automated Learning
• +۶ مورد دیگر

Marimuthu Palaniswami is a Professor in the Department of Electrical and Electronic Engineering at the University of Melbourne, specializing in IoT, sensor networks, and computational intelligence. He leads large-scale research initiatives, including the ARC Research Network ISSNIP and the Centre of Excellence for Networked Decision Systems (CENDS). His work spans infrastructure, smart cities, healthcare, and environmental monitoring, with over 400 publications in top-tier journals and conferences. Education Ph.D., University of Newcastle, Australia Masters (Research), University of Melbourne Masters (Coursework), Indian Institute of Science Bachelor of Engineering (Honours), University of Madras Research Focus His research translates into deployable technologies for societal impact, including smart city projects (e.g., European Union's FP7 Smart Santander), healthcare diagnostics (e.g., CSIRO/Microsoft fetal monitoring tools), and environmental monitoring (Great Barrier Reef initiatives). He emphasizes interdisciplinary collaboration, leveraging IoT and AI for healthcare, transport, and governance. Recent Projects Developing Non-Invasive Diagnostics to Prevent Stillbirth (2019–2025) Hydrogen Storage Using Concrete Composites (2022–2025) Academic Centres of Cyber Security Excellence (2024–2026) Awards & Recognition Fellow of IEEE (2013–2015 Distinguished Lecturer) Knowledge Transfer Excellence Awards (2008, 2008, 2010) Recipient of multiple government and industry grants totaling millions in funding Professional Contributions Co-founder of the European IoT Forum, former co-director of CENDS, and advisor to EU and U.S. projects. Has organized over 10 IEEE conferences and served on NSF and EU panels. Labs & Teams Leads interdisciplinary teams in IoT, healthcare technology, and sensor networks, fostering collaborations with industry partners like Arup and Microsoft Research.

Marcela Suarezمشاهده پروفایل

عضو هیئت علمی

• Spatial Data Science
• Geographic Information Science
• Cartography
• +۳ مورد دیگر

Marcela Suarez is an Assistant Teaching Professor of Spatial Data Science in the Department of Geography at The Pennsylvania State University, affiliated with the John A. Dutton e-Education Institute. She teaches courses on cartography, GIS, and spatial data analysis in online geospatial programs. Her research focuses on integrating geographic information science, cartography, and emergency management to analyze user-generated content and volunteered geographic information for decision-making in disaster response. Suarez earned her Ph.D. in Geography from the University of California, Santa Barbara (2020), an M.Sc. in Disaster Risk Management and Emergency Response from the University of Costa Rica (2011), and a B.Eng. in Cadastral Engineering and Geodesy from Universidad Distrital Francisco José de Caldas, Colombia (2005). Prior roles include Research Specialist at UCSB’s Center for Spatial Studies and consultancy for the UNDP’s Colombian Climate Adaptation Project. She has led outreach initiatives like the GeoClub Colombia, empowering high school students through geography education. Her work emphasizes geovisualization, spatial clustering, and data fusion techniques to enhance emergency management and social-environmental analysis. Research highlights include leveraging social media data for disaster response and spatial vulnerability assessments in urban and environmental contexts. Her contributions bridge academic research with practical applications in risk mitigation and community resilience.

Maria A. Zuluagaمشاهده پروفایل

مدرس

• Data Science
• Medical Imaging
• Machine Learning
• +۴ مورد دیگر

Maria A. Zuluaga is a Lecturer in Data Science at EURECOM, leading the groundbreaking Caravel project funded by a prestigious ERC Consolidator Grant (2024). This €2 million initiative aims to construct a spatio-temporal atlas of the cerebral vascular system using AI-driven analysis of MRI scans from 50 volunteers aged 25-70, in collaboration with King's College London and Nice University Hospital. Her research bridges computer science and medical applications, focusing on extracting and characterizing complex cerebral vascular structures through artificial intelligence. The Caravel project seeks to overcome current imaging limitations by developing standardized tools that work across multiple imaging modalities, with the ultimate goal of creating the largest neurovascular database ever assembled (over 50,000 images). ERC Consolidator Grant recipient (2024), the only French computer science project selected that year Developing open-access vascular atlas for global medical research Focus on detecting early signatures of neurological conditions including stroke and Alzheimer's disease Zuluaga previously worked in industry at Amadeus in Nice before returning to academia, bringing valuable cross-sector experience to her ERC application. She is deeply committed to open science, stating: "If I make this atlas and keep it for myself, it has no impact. I want it to serve medical research worldwide." Her work represents a convergence of geographical exploration (as a Colombian researcher studying brain "vessels"), scientific inquiry, and technological innovation.

Dimitrios Michailمشاهده پروفایل

دانشیار

• Algorithms
• Graph Algorithms
• Machine Learning
• +۶ مورد دیگر

Dimitrios Michail is an Associate Professor in the Department of Computer Science and Telecommunications at Harokopio University. He holds a Diploma in Electronic Engineering and Computer Engineering from the Polytechnic University of Crete, a Master's in Computer Science, and a Ph.D. in Algorithms from the Max-Planck Institute for Computer Science. His research focuses on algorithms for modern computational models, graph algorithms, machine learning, and their applications in computer vision, wildfire prediction, and social network analytics. He has been involved in European projects like TELEIOS and DeepCube. His work intersects earth observation, autonomous systems, and AI-driven solutions for environmental challenges. Recent research includes Earth-as-a-Graph frameworks for wildfire forecasting and novel datasets for InSAR analysis. He has contributed to libraries like JGraphT and JHeaps, emphasizing algorithmic efficiency and open-source tools. Michail's publications span graph theory, deep learning, and remote sensing applications, with a focus on real-world problems like flood mapping and fake news detection. He has collaborated on projects addressing urban mobility, public transport optimization, and disaster preparedness through spatio-temporal modeling.

Roger Zimmermannمشاهده پروفایل

استاد

• Multimedia and Distributed Systems
• Multimedia and Mobile Networking
• Spatio-temporal Data Management
• +۸ مورد دیگر

Roger Zimmermann is a Full Professor at the School of Computing, National University of Singapore (NUS), where he is also a Co-PI at the Grab-NUS AI Lab and leads the Location AI project. He previously served as Deputy Director of the NUS Smart Systems Institute (SSI) and Co-Director of the Centre of Social Media Innovations for Communities (COSMIC), both funded by Singapore’s National Research Foundation (NRF). Before joining NUS, he was a Research Area Director and Research Assistant Professor at the University of Southern California (USC). Ph.D. in Computer Science, University of Southern California (1998) M.S. in Computer Science, University of Southern California (1994) His research focuses on multimedia systems , spatio-temporal data management , streaming media architectures (especially DASH), machine learning applications , AR/VR , and location-based services . He leads the Media Management Research Lab (MMRL) at NUS, which conducts cutting-edge work in distributed multimedia and intelligent systems. His work combines theoretical depth with real-world applications in urban computing, smart mobility, and immersive media. The recent publications reflect a strong trend toward multimodal learning , spatio-temporal AI , adaptive streaming , and urban intelligence . His team explores zero-shot learning, 3D scene understanding, traffic forecasting, and open-vocabulary audio-visual segmentation, often leveraging foundational models and deep neural architectures. There is a clear emphasis on real-time, scalable systems for smart cities and immersive experiences. Dr. Zimmermann has received numerous accolades, including: DASH-IF Excellence in DASH Award (multiple years) Best Paper Awards at ACM SIGSPATIAL, IEEE ICME, and ACM MMSys Silver Award at ACM MMSys 2020 Grand Challenge IEEE Communications Society Best Editor Award (2017) ACM Distinguished Member (2017) Top 1% Publons Reviewer in Computer Science (2018) He has advised numerous students and led major research initiatives funded by MOE, NRF, A*STAR, NSF, and industry partners like Seagate, Intel, and HP. He has served as General Chair for IEEE MIPR 2023, ACM Multimedia 2020, and IEEE ISM 2015, and as TPC Co-Chair for several top-tier conferences. His editorial roles include Associate Editor for IEEE Transactions on Multimedia (TMM), ACM TOMM, and IEEE OJ-COMS. He leads the Media Management Research Lab (MMRL) , which focuses on intelligent multimedia systems, spatiotemporal data mining, and immersive media technologies. The lab develops scalable solutions for real-world challenges in urban computing, smart transportation, and interactive media.

Giovanna Guerriniمشاهده پروفایل

دانشیار

• Data Management
• Large Scale Data Management
• Semantic Data Management
• +۱۵ مورد دیگر

Giovanna Guerrini is an Associate Professor in the Department of Informatics, Bioengineering, Robotics, and Systems Engineering (DIBRIS) at the University of Genoa, Italy. She is actively involved in research, teaching, and academic service, with leadership roles in major conferences such as EDBT (Executive Board Member and Treasurer), SOFSEM (Track Chair), and UMAP (Workshop Chair). Her research interests include: Data Management Large Scale and Semantic Data Management Approximate and Adaptive Query Processing Linked Data and Ontology Matching Graph Matching and Geospatial Ontologies Spatio-Temporal Data and Location Inference Computer Science Education and Computational Thinking Her recent publications show a growing focus on computer science education, particularly in using gamified and extended reality environments, Sonic Pi for teaching concurrency, and AI-driven tools for enhancing computational thinking. This reflects a shift toward pedagogical innovation and student-centered learning methodologies. She has been recognized through active participation in top-tier program committees (SIGMOD, ISWC, ICDE) and organizing key workshops and schools (EDBT School 2017, APCSE at UMAP). No formal scientific awards are listed in the provided text. She advises multiple PhD students, both current and past, and contributes to academic grants and collaborative projects, particularly in database education and data science initiatives. She is affiliated with research groups including the DaMA Research Group, Data Science and Engineering Research Program, Big Data Interest Group UniGe, and CINI Big Data Research Lab.

Claudio SILVESTRIمشاهده پروفایل

دانشیار

• Data Mining
• Privacy in Location-Based Services
• Spatio-Temporal Data Analysis
• +۳ مورد دیگر

Claudio SILVESTRI is an Associate Professor at Ca' Foscari University of Venice, affiliated with the Department of Environmental Sciences, Computer Science and Statistics. He specializes in Computer Science (INFO-01/A), with a focus on data mining, privacy in location-based services, and spatio-temporal data analysis. His research integrates computer science with environmental and biomedical applications. Teaching Responsibilities include courses on Advanced Data Management (Computer Science) and Geographic Information Systems (Environmental Sciences) at the Master's level across multiple academic years. Research Interests span: Algorithms for privacy protection in location-based services Spatio-Temporal Data Warehouses and trajectory analysis Parallel computing on GPU and cloud platforms Applications in fisheries monitoring and diabetic kidney disease modeling Funding Projects include EU initiatives like H2020 (e.g., DC-ren for kidney disease research) and regional grants (e.g., ADMIN4D on Industry 4.0). Key collaborations involve researchers like Salvatore ORLANDO and Debora SLANZI. He is affiliated with the European Center for Living Technology (ECLT) and the Research Institute for Social Innovation. Office hours are held Wednesdays 2-4 PM by email appointment.

Yichuan Zhuمشاهده پروفایل

استادیار

• Machine Learning in Geotechnical Engineering
• Computational Geomechanics
• Uncertainty Quantification
• +۹ مورد دیگر

Yichuan Zhu is an Assistant Professor in the Department of Civil and Environmental Engineering at Temple University's College of Engineering. He leads the Computational Geosystems Group (CGG), focusing on interdisciplinary research at the intersection of civil engineering, geosciences, and computer science. Research Interests: Dr. Zhu’s work centers on applying machine learning, uncertainty quantification, and computational modeling to geotechnical and geological challenges. Key areas include granular mechanics, landslide characterization, remote sensing applications, risk and reliability assessment, and AI-driven geosystem modeling. His research combines physical principles with data-driven techniques to enhance predictive accuracy and decision-making in complex earth systems. Publication Trends: His recent publications (2021–2025) reflect a strong emphasis on integrating machine learning (including transformers and Bayesian deep learning) with traditional geomechanical models. Topics span tunnel safety, jet grouting, seismic site response, and landslide susceptibility, demonstrating a consistent focus on uncertainty-aware, AI-enhanced solutions for geotechnical problems. Professional Recognition and Activities: Chair, Session MS 0706 (Natural Hazards), EMI/PMC 2024 Conference Presented at Geotechnical Frontiers 2025 and Geo-Congress 2024 Actively recruiting fully-funded Ph.D. students Advising and Teaching: Dr. Zhu advises Ph.D. students, including Dr. Khabiri, whose dissertation informed recent conference presentations. He teaches core undergraduate and graduate courses in soil mechanics, foundation engineering, and geotechnical earthquake engineering (CEE 2011, CEE 3331, CEE 4821–4823, CEE 5821–5823). His lab, the Computational Geosystems Group, supports ongoing research in AI and computational geosciences. Research Group: The Computational Geosystems Group (CGG) conducts cutting-edge research in probabilistic modeling, geosystem simulation, and data-driven geotechnics. The team is actively expanding, with funded positions available for graduate researchers.

• Sexology
• Gender Studies
• Behavioral Sciences
• +۳ مورد دیگر

Christian Graugaard is a Professor of Sexology at Aalborg University, affiliated with the Faculty of Medicine and the Department of Clinical Medicine. He is a key member of the Center for Sexology Research and leads Project SEXUS, aiming to study Danish sexual behavior comprehensively. His work emphasizes the intersection of biological, psychological, and cultural factors in human sexuality, challenging simplistic gender-based stereotypes. Research interests include gender differences in sexual behavior, societal norms influencing sexual health, and the cultural dimensions of human sexuality. He actively participates in public discourse, as seen in his DR-podcast interview on 'Ramt af kærlighed,' where he discussed the complex interplay between biology and culture in shaping sexual identities. Though no specific awards or grants are detailed here, his publications span advanced technical domains like spatiotemporal data analysis, federated learning, and trajectory modeling, suggesting interdisciplinary research collaborations. His work on systems like OneDB and SWASH highlights contributions to distributed computing and data science, which may underpin his methodologies in large-scale sexual behavior studies. He currently holds no listed students or formal advisees in the provided texts, and his involvement in labs/teams is limited to the Center for Sexology Research and Project SEXUS.

Shuang Aoمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Reinforcement Learning
• Curriculum Learning
• +۴ مورد دیگر

Mr. Shuang Ao is a Postdoctoral Research Fellow at the School of Computer Science and Engineering, University of New South Wales (UNSW Sydney). He earned his PhD from the University of Technology Sydney in January 2024. His research focuses on machine learning, reinforcement learning, and curriculum learning, with applications in robotic control and antibody drug discovery. Research Interests: Machine Learning Reinforcement Learning Curriculum Learning Graph Algorithms Optimization Techniques Recent Publication Trends: Shuang's work spans large language models for location-based recommendations, spatio-temporal forecasting, reinforcement learning frameworks, and graph algorithm optimizations. His articles address both theoretical advancements and practical applications in scalable systems and data analysis. Contact: Email: shuang.ao@unsw.edu.au

Chalkias Christosمشاهده پروفایل

استاد

• Geographic Information Systems
• Applied Geography
• Spatial Analysis
• +۳ مورد دیگر

Christos Chalkias serves as Professor and Vice-Rector for Research, Development and Lifelong Learning at Harokopio University's Department of Geography. Based in Athens, Greece, his academic office is located in the Library Building (Office 4.5). His educational background includes a Degree in Geology (1991) and PhD in Physical Geography & Geoinformatics (1996), both completed at the National and Kapodistrian University of Athens. His research encompasses diverse geospatial domains with particular emphasis on: Geographic Information Systems & Science – Developing spatial analysis methodologies Applied Geography – Solving real-world environmental and societal challenges Spatial Analysis – Examining geographic patterns and processes Environmental Modeling – Simulating physical phenomena Health Geography – Analyzing spatial health disparities Digital Cartography – Innovating map visualization techniques Recent publications (2023-2025) demonstrate strong focus on geospatial applications in health epidemiology, environmental monitoring, and disaster management. His work frequently employs remote sensing, spatial statistics, and GIS technologies to address Mediterranean-region challenges including cardiovascular disease patterns, light pollution, soil degradation, and earthquake impacts. Distinct research trends include historical geospatial reconstruction, nocturnal earth observation, and community-engaged environmental sensing.