جست‌وجوی استاد و پژوهشگر

Cuneyt Gurcan Akcoraمشاهده پروفایل

دانشیار

• Data Science on Complex Networks
• Graph Mining
• Topological Data Analysis
• +۳ مورد دیگر

Cuneyt Gurcan Akcora is an Associate Professor of Computer Science at the University of Central Florida (UCF) and an Adjunct Professor in Computer Science and Statistics at the University of Manitoba, Canada. He holds a Ph.D. from Università degli Studi dell’Insubria (Italy) and an M.S. from SUNY Buffalo (USA) as a Fulbright Scholar. His research focuses on data science applied to complex networks and graph mining, particularly in blockchain and online social networks. He has collaborated with institutions like Yahoo! Research Barcelona, Qatar Computing Research Institute, and Huawei. Education: PhD in Computer Science, 2014 – Università degli Studi dell’Insubria, Italy MEng in Computer Science, 2010 – SUNY Buffalo, USA BSc in Electrical & Electronics Engineering, 2008 – Karadeniz Technical University, Turkey Research Interests: Explainable AI and Graph Machine Learning Topological Data Analysis (TDA) for Blockchain Networks Large-Scale Graph Analysis and Anomaly Detection Nonparametric Statistical Methods Key Contributions: His work includes developing chainlet theory for Bitcoin price prediction, scalable TDA algorithms for blockchain forensics, and interdisciplinary grants exploring blockchain applications in insurance. Notable projects include the Chartalist Dataset for blockchain network analysis and ChainNet , a topological graph learning framework. Awards & Grants: NSERC Discovery Grant (2020) UCF Interdisciplinary Grant for Blockchain in Insurance (2020) Fulbright Scholarship (M.S., SUNY Buffalo) Labs & Teams: Active in UCF’s FData Lab and leads blockchain data analytics initiatives. His work bridges academia and industry through collaborations with Huawei, QCRI, and others.

Emily Kangمشاهده پروفایل

استاد

• Spatial Statistics
• Environmental Statistics
• Data Assimilation
• +۲ مورد دیگر

Emily Kang is a Professor in the Department of Mathematical Sciences at the University of Cincinnati, where she leads the Group on Data Analytics and Decision Sciences (GDADS). Her research develops statistical methodologies for spatial and spatio-temporal data, with applications in environmental science, climate modeling, and remote sensing. Kang specializes in hierarchical Bayesian models, data assimilation techniques, and scalable algorithms for large environmental datasets. Her work includes developing the EcoPro framework for ecological projections using Earth system models and remote sensing data, creating statistical downscaling methods for climate variables, and designing visualization tools for global environmental data on multi-resolution grids. Kang received the American Statistical Association's ENVR Early Investigator Award for contributions to environmental statistics. Current projects focus on neighborhood-scale extreme heat projections, coral reef habitability under climate change, and recursive co-kriging models for multi-fidelity spatial data. Her research advances uncertainty quantification in remote sensing products and climate impact assessments.

• Artificial Intelligence
• Geospatial Data Science
• Knowledge Graphs
• +۵ مورد دیگر

Professor Manolis Koubarakis is a faculty member at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on geospatial data science, knowledge graphs, entity resolution, and AI applications in Earth observation. He leads projects like ExtremeEarth and Plato, advancing semantic data cube systems and geospatial question answering engines. His work bridges AI and geospatial technologies, with contributions to frameworks like pyJedAI and Strabo 2 for managing big geospatial data. Research Interests include: Geospatial Question Answering Systems Entity Resolution and Entity Linking Ontology-Based Data Access (OBDA) Knowledge Graph Construction and Applications Earth Observation Data Analytics AI for Geoinformatics Notable Projects: ExtremeEarth: Combines Copernicus satellite data with machine learning for environmental analytics. Plato: Semantic data cube system enabling advanced querying of multidimensional datasets. GeoQA2: A geospatial question answering engine evaluated on large benchmarks. JedAI Family: Tools for scalable entity resolution in structured/semi-structured data. His publications span 20+ years, with recent emphasis on: AI-driven Earth observation systems Geospatial RDF benchmarking 3D geospatial interlinking Large language models for legal and health content delivery

Djamel E. Khelladiمشاهده پروفایل

پژوهشگر

• Software Engineering
• Model-Driven Engineering
• Software Evolution
• +۶ مورد دیگر

Djamel E. Khelladi is a CNRS researcher affiliated with the IRISA research lab and the DIVERSE team at University of Rennes 1 , France. Previously, he held postdoctoral and PhD positions at Johannes Kepler University (JKU) Linz, Austria, and Université Pierre et Marie Curie (UPMC), France. Research interests include: Model-Driven Engineering Software Evolution & Co-evolution AI and Generative AI Applications Polyglot Programming Digital Twins Recent article trends focus on integrating Large Language Models (LLMs) for code-metamodel co-evolution, polyglot programming challenges, incremental build optimization in configurable systems, and empirical studies on software evolution. His work often bridges theoretical modeling with practical implementation in industrial contexts. Academic service roles include: Proceedings Co-Chair @MODELS 2025 Co-Organizer of Models and Evolution (ME) workshops (2023-2025) Co-Editor for special issue on Model Driven Engineering for Digital Twins (SoSym 2024/25) PC member in top venues: ICSE , ASE , MODELS , ECMFA , MSR , FSE

• Healthcare workforce
• Opioid use disorder and policy implications
• Medicare and long-term care
• +۷ مورد دیگر

Ulrike Muench is an Associate Professor with tenure in the Department of Social and Behavioral Sciences at the UCSF School of Nursing, with affiliations at the Philip R. Lee Institute for Health Policy Studies and Healthforce Center. She specializes in nursing workforce dynamics, opioid policy, Medicare systems, and disparities in healthcare. Her research leverages large datasets like Medicare claims and the Medical Expenditure Panel Survey. Education & Training: MSN (2005) and PhD (2012) in Nursing from Yale University Postdoctoral Fellowship (2014) at Vanderbilt University School of Nursing Research Interests: Focuses on nurse practitioner roles, prescribing patterns in primary care/nursing homes, dementia care trajectories, and gender-based pay disparities in healthcare. Her work bridges health policy analysis with real-world clinical outcomes, aiming to inform equitable healthcare delivery systems. Awards: 2016 Academy Health New Investigator Award 2018 American Academy of Nursing Fellow 2019 UCSF School of Nursing Mentoring Award Grants & Advising: Leads studies funded by NIH and foundations, mentoring early-career researchers in health services research. Collaborates on projects addressing workforce distribution, rural-urban care disparities, and policy reform. Labs/Teams: Active in UCSF's Healthforce Center, focusing on healthcare workforce analytics and interdisciplinary policy development.

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Dr. Masoud Makrehchi is an Associate Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University, part of the Faculty of Engineering and Applied Science. His research focuses on Natural Language Processing, Artificial Intelligence, Machine Learning, and Social Computing, with a strong emphasis on applications in network science and moral AI. He holds a PhD from the University of Waterloo (2007), along with earlier degrees from Shiraz University and Iran University of Science and Technology. Prior to academia, he worked as a Senior Research Scientist at Thomson Reuters (2008–2012) and completed a postdoctoral fellowship at the University of Waterloo (2007–2008). His research expertise includes text mining, social network analysis, and network science, addressing challenges such as signed social network analysis, document classification, and crime trend prediction using social media data. He has received several awards, including the NSERC Postgraduate Scholarship and the SBP Challenge Award (2012). His work spans over 50 peer-reviewed publications in journals like Expert Systems with Applications, Social Network Analysis and Mining, and Web Intelligence, with contributions to conferences such as GECCO and IEEE/ACM. Dr. Makrehchi’s publications highlight innovations in feature selection, text segmentation, and AI-driven frameworks for requirements elicitation. His recent work explores coherence graphs for text segmentation, generative AI in education, and bias detection in medical datasets. He has also contributed to patent applications related to sentiment analysis and text extraction systems.

Bermond Scogginsمشاهده پروفایل

پژوهشگر ارشد

• Political Behavior
• Survey Experiments
• Democratic Backsliding
• +۱ مورد دیگر

Bermond Scoggins is a Research Fellow at the School of Politics and International Relations, College of Asia and the Pacific, Australian National University. He holds a BA (Honours) from ANU and specializes in political behavior research using survey experiments and meta-analytic methods. His research investigates democratic backsliding mechanisms, causal inference in political systems, and voter decision-making processes in democratic contexts, with special focus on Southeast Asian political systems. Recent publications examine global science communication patterns, public trust in scientists, and methodological transparency in social sciences, utilizing large-scale international datasets and cross-national comparative frameworks.

Christian Wachingerمشاهده پروفایل

استاد

• Artificial Intelligence
• Medical Imaging
• Machine Learning
• +۳ مورد دیگر

Prof. Christian Wachinger is a Professor of Artificial Intelligence in Radiology at the Technical University of Munich (TUM), part of the TUM School of Medicine and Health. His research focuses on developing AI algorithms for medical imaging, disease prediction, and addressing challenges like AI transparency and data bias. He holds a PhD in Medical Image Processing from TUM and completed postdoctoral training at MIT and Harvard Medical School. Notable awards include the Feodor Lynen Fellowship and Siemens Excellence Award. His lab, Artificial Intelligence in Medical Imaging, pioneers innovations in multimodal data integration and clinical AI applications. Education: PhD in Medical Image Processing, TUM (2011) Diploma in Computer Science, TUM and ENST Paris Honors Degree in Technology Management, CDTM Research Interests: Prof. Wachinger's work bridges AI and medicine, emphasizing neuroimaging, generative models, and clinical translation. Key areas include bias correction in medical datasets, multimodal fusion (MRI/PET), and explainable AI for healthcare. Awards: Feodor Lynen Research Fellowship (2011) German Computer Science Society Award (2011) Siemens Excellence Award (2007) Junior Research Group, Bavaria Center for Digitalization (2017) Grants & Labs: Leads the AI in Medical Imaging lab at TUM, with projects funded by grants focusing on AI-driven diagnostics and healthcare innovation.

Mark Meekanمشاهده پروفایل

پژوهشگر ارشد

• Marine Conservation Biology
• Elasmobranch Ecology
• Coral Reef Fish Ecology
• +۳ مورد دیگر

Dr Mark Meekan is an Adjunct Senior Research Fellow at the UWA Oceans Institute, The University of Western Australia. He holds a PhD in Environmental Sciences from Griffith University (1993), focusing on coral reef fish population dynamics. With over 30 years of expertise, his research spans tropical marine ecosystems, elasmobranch ecology, and coral reef conservation. He supervises post-doctoral and PhD students globally, contributing to projects on sharks and reef fish across the Indian and Pacific Oceans. His research interests include elasmobranch population dynamics, behavioral ecology, and threatened species conservation. He serves as Chief Specialist Editor for Frontiers in Marine Science’s Marine Megafauna section. Key areas of focus are predator-prey interactions, coral reef health, and the ecological impacts of climate change. He has authored over 300 peer-reviewed articles and led collaborative projects on marine megafauna movement, anthropogenic threats, and ecosystem resilience. Recent work highlights include studies on whale shark habitat connectivity, tiger shark distribution drivers, and the ecological consequences of predator removals on coral reefs. He actively engages in global marine conservation initiatives, emphasizing the need for evidence-based management strategies to protect marine biodiversity. His contributions extend to acoustic telemetry networks and large-scale experiments assessing seismic survey impacts on marine life. Dr Meekan collaborates internationally, with projects in Australia, Seychelles, and the Red Sea. His work addresses Sustainable Development Goals related to life below water (SDG 14), particularly marine ecosystem preservation and sustainable fisheries. Grants include studies on shark population dynamics and marine reserve effectiveness, funded by institutions like the Minderoo Foundation and WA Department of Environment. He leads datasets and projects on manta ray behavior, coral reef recovery, and whale shark collision risks with shipping. His research underscores the critical role of marine megafauna in maintaining healthy ecosystems, advocating for integrated conservation approaches to mitigate human-induced environmental changes.

Erik Rosenqvistمشاهده پروفایل

استادیار

• Educational Inequality
• School Segregation
• Peer Effects
• +۲ مورد دیگر

Erik Rosenqvist is Assistant Professor at Linköping University's Institute for Analytical Sociology, examining how educational systems reproduce social inequality. Research investigates school composition effects, peer influence on educational decisions, and socioeconomic achievement gaps. Current project compares educational reforms' impact on segregation in Scandinavian countries. Methodological expertise includes quasi-experimental designs analyzing large-scale educational datasets. Published in leading sociology journals on grading equity and school choice impacts.

Siran M. Koroukianمشاهده پروفایل

استاد

• Multimorbidity in older adults
• Healthcare disparities
• Health services research
• +۳ مورد دیگر

Siran M. Koroukian, PhD, is a Professor in the Department of Population and Quantitative Health Sciences at Case Western Reserve University's School of Medicine. She also holds roles as Professor in the Center for Community Health Integration and Secondary Faculty in the Jack, Joseph and Morton Mandel School of Applied Social Sciences. Her research bridges public health and big data/informatics to address disparities in healthcare access and outcomes, particularly in chronic illnesses like cancer and epilepsy among older adults. Key contributions include methodologies for evaluating multimorbidity (co-occurring chronic conditions, functional limitations, and geriatric syndromes) and infrastructure development for health services research. Education: PhD in Health Services Research (Case Western Reserve University, 1999) MHA from Cornell University (1987) Bachelor's/Master's in Nursing from Université St. Joseph (1982/1986) National Cancer Institute Postdoctoral Fellowship (2002) Research Focus: Health disparities in access/outcomes for chronic diseases (e.g., cancer, epilepsy) Medicare/Medicaid program evaluations Methodological innovations using large datasets (e.g., Medicare claims, tumor registries) Awards: 2011 Clinical Quality Award (Ohio Department of Mental Health) National Institute on Aging Career Development Award (2005) National Cancer Institute K07 Grant (2007) Sloan Program International Prize (1987) Grants & Collaborations: CDC-funded study on epilepsy treatment gaps NHLBI project on cardiovascular hospitalizations Multidisciplinary work with Cleveland Clinic, NIH, and international partners Teaching: Courses include secondary analysis of healthcare data, epidemiology, and population health strategies.

Didong Liمشاهده پروفایل

استادیار

• Biostatistics
• Machine Learning
• Geometric Data Analysis
• +۷ مورد دیگر

Dr. Didong Li is an Assistant Professor in the Department of Biostatistics at the Gillings School of Global Public Health , University of North Carolina at Chapel Hill. His research focuses on statistical methods for complex data, including manifold learning, nonparametric Bayesian inference, and spatial statistics, with applications in healthcare, genomics, and environmental health. He holds a PhD in Mathematics from Duke University (2020), and degrees from Beijing Institute of Technology (BS 2012, MS 2015). His research interests include dimension reduction, Gaussian processes, geometric data analysis, and network analysis. He has developed novel methods for analyzing electronic health records, single-cell RNA sequencing data, and spatial omics datasets. Notable contributions include the spherelet manifold approximation framework and the STimage-1K4M dataset. Dr. Li has received the Inaugural IMS Lawrence D. Brown PhD Student Award (2019) . He serves on the editorial board of the Journal of Machine Learning Research and organized sessions at JSM 2021-2022 on geometric Bayesian methods. His lab supports interdisciplinary collaborations, with ongoing projects in spatial transcriptomics, healthcare access analysis, and AI-driven medical informatics. Advising highlights include guiding students through successful PhD defenses (e.g., Dr. Sam Hawke, Dr. Jiawen Chen) and postdoctoral placements. His team secured a NVIDIA Academic Grant (2024) for multi-modal AI in spatial transcriptomics. The Li Lab maintains active partnerships with institutions worldwide, advancing both statistical theory and real-world applications.

• Environmental Surveillance Monitoring
• Ecological Data Standardization
• Remote Sensing
• +۷ مورد دیگر

Associate Professor Ben Sparrow is affiliated with the University of Adelaide's School of Biological Sciences within the Faculty of Sciences, Engineering and Technology. He leads the TERN Ecosystem Surveillance program, focusing on environmental monitoring methodologies and data standardization. His work emphasizes integrating remote sensing technologies with ecological data to improve biodiversity tracking and policy development. Ben has extensive experience in grant-funded research, including leadership roles in TERN's AusPlots and Eco-informatics initiatives, and has contributed to projects like the Global Drylands Assessment with the UN FAO. He collaborates with stakeholders to address socio-ecological challenges in environmental management and has advised Honours students on topics related to natural resource management and ecological data analysis. Research Interests : Ben's research centers on environmental surveillance, ecological monitoring standardization, remote sensing applications, citizen science integration, and understanding climate change impacts on Australian flora. He advocates for adaptable protocols that balance national data consistency with regional autonomy, ensuring ecological data supports both science and policy. His work includes developing open-access datasets (e.g., deadtrees.earth) and advancing tools like the ausplotsR package for vegetation analysis. Grants & Funding : Recent grants include $2.1M from NCRIS/TERN (2018), a $484,770 Citizen Science Grant for the Wild Orchid Watch project, and UN FAO funding ($20,000 USD) for global drylands research. He has also secured funding for LiDAR and photogrammetry initiatives, vegetation mapping projects, and cross-disciplinary research efforts. Professional Activities : Ben actively participates in committees such as the Enabling ecosystem surveillance working group (Ecosystem Science Council) and the Drylands Working Group (UN FAO). He co-chaired the 15th Australasian Remote Sensing and Photogrammetry Conference and contributes to global initiatives like the sPlot dataset project. His work bridges ecological science with practical policy applications, emphasizing reflexivity and communication in socio-ecological systems. Labs/Teams : Ben is part of the Terrestrial Ecosystem Research Network (TERN) team at the University of Adelaide's Waite campus, leading the Ecosystem Surveillance unit. He collaborates with the AusPlots Rangelands program and the Eco-informatics group to develop continental-scale ecological monitoring infrastructure.

Nassim Bozorgniaمشاهده پروفایل

استادیار

• Astroparticle Physics
• Dark Matter Phenomenology
• Cosmology
• +۳ مورد دیگر

Nassim Bozorgnia is an Assistant Professor in the Department of Physics at the University of Alberta and a Tier 2 Canada Research Chair in Astroparticle Physics. He specializes in theoretical astroparticle physics and dark matter phenomenology, focusing on dark matter's particle nature and its implications for direct/indirect detection experiments. His research uses cosmological simulations and observational data to study dark matter distribution in galaxies like the Milky Way. Education: Ph.D. in Physics, UCLA (2012), Dissertation: 'Ion Channeling in Direct Dark Matter Detection' M.S. in Physics, San Francisco State University (2006) B.S. in Physics, Kharazmi University (2004) Research Interests: His work explores dark matter interactions, galactic distribution modeling, and astroparticle physics. Key areas include: Dark matter direct detection using crystal detectors Impact of Large Magellanic Cloud on dark matter signals Velocity-dependent annihilation radiation Dark matter distribution correlations with stellar kinematics Grants & Awards: Canada Research Chair (2022–2027) Natural Sciences and Engineering Research Council (NSERC) Discovery Grant (2020–2025) McDonald Institute Highly Qualified Personnel Pooled Resources (2021–2023) Recipient of multiple fellowships including UCLA's Cota Robles Fellowship Teaching & Supervision: Currently supervising 6 Ph.D./M.S. students and mentoring EXPLORE program participants Teaches courses like 'Physical Cosmology' and 'Dark Matter: from cosmology to underground searches' Developed the EXPLORE international research collaboration program Labs & Collaborations: Active in collaborations like the EXPLORE program and international initiatives such as GRAPPA and IPPP. His work integrates cosmological simulations (EAGLE, APOSTLE) with observational datasets to refine dark matter models.

• Clinical Immunology
• Blood Donation Research
• Infectious Diseases
• +۵ مورد دیگر

Bitten Aagaard Jensen serves as a Leading Senior Physician (Ledende overlæge) at Aalborg University Hospital within The Faculty of Medicine's Department of Clinical Immunology. She maintains an active research profile with 48 publications documented through 2025 and has contributed to 6 significant datasets, particularly related to SARS-CoV-2 antibody research. Her research interests span Clinical Immunology, Blood Donation Research, Infectious Diseases, and Inflammatory Diseases. She has been particularly active in studying blood donor health, SARS-CoV-2 seroprevalence in vulnerable populations, and genetic associations with immunological conditions. Her work often involves large-scale epidemiological studies with thousands of participants. Dr. Jensen's publication record shows consistent productivity, with 17 publications in 2025 alone (as of the data collection), 10 in 2024, 4 in 2023, and 8 in 2022. Her research frequently appears in high-impact journals including Journal of Allergy and Clinical Immunology, Scientific Reports, European Journal of Epidemiology, Clinical Microbiology and Infection, and BMJ Open Gastroenterology. Extensive work on SARS-CoV-2 antibody prevalence in vulnerable populations including social housing residents and homeless individuals Research on blood donor health parameters and safety Genetic studies related to inflammatory conditions Investigations into infectious disease markers and immune responses Her media presence includes coverage in 6 news outlets regarding blood donor coronavirus testing in 2020, demonstrating her engagement with public health communication. She collaborates extensively with researchers across Denmark, particularly with colleagues at blood banks, university hospitals, and epidemiological research centers.