جست‌وجوی استاد و پژوهشگر

• Machine Learning
• Computer Vision
• Artificial Intelligence
• +۴ مورد دیگر

Manuel Felipe Muciéntes Molina is a Professor of Computer Science and Artificial Intelligence at the Research Center on Intelligent Technologies (CiTIUS), University of Santiago de Compostela (USC). He holds a PhD from USC (2002) focusing on fuzzy logic-based control systems for autonomous robots. His research emphasizes machine learning applications in computer vision, process mining, robotics, and healthcare. He teaches courses like Statistical Learning, Supervised Machine Learning, and Deep Learning. Key Projects: RAI4P: Responsible AI for Process Mining 2.0 QC4SUSTEX: Authentication and security of sustainable textiles CAREBOT: Intelligent robotic units for hospital care Research Interests: Machine learning, computer vision (object detection, tracking), process mining, robotics navigation, and healthcare AI applications. Labs/Teams: Leading the Grupo GSI (Systems Intelligence) within CiTIUS, focusing on intelligent systems and AI-driven solutions.

JOSE RAMON RIOS VIQUEIRAمشاهده پروفایل

استاد

• Spatial Data Management
• Environmental Data Integration
• Geographic Information Systems (GIS)
• +۶ مورد دیگر

Jose Ramon Rios Viñuela is a Professor at the Department of Electronics and Computing, University of Santiago de Compostela, affiliated with the Higher Technical School of Engineering. He holds a PhD from the University of A Coruña (2003) for his thesis on spatio-temporal data management. His research focuses on spatial databases, environmental data integration, smart city technologies, geographic information systems (GIS), and spatio-temporal data modeling. Key projects include TRAFAIR (traffic-air quality analysis), COGRADE research group (computer graphics and data engineering), and GeoHbbTV frameworks for geospatial interactive media. He leads efforts in distributed spatial data processing, semantic interoperability, and sensor network integration for environmental monitoring. Notable contributions include frameworks like TAQE (traffic-air quality modeling), GeoSPARQL query systems, and MeteoSIX meteorological platforms. His work bridges earth sciences with public accessibility through smart environmental infrastructures, emphasizing citizen engagement and open data dissemination. Current research trends explore big data analytics for geospatial applications, federated environmental data systems, and low-cost sensor networks for urban sustainability. He collaborates on projects involving air quality forecasting (GRAL model), spatial join optimization in large data lakes, and semantic mediation of environmental observation systems. His academic contributions span over 60 peer-reviewed publications across GIS, database systems, and environmental informatics.

Natalia Baileyمشاهده پروفایل

مدرس ارشد

• Cross-sectional dependence
• Factor models
• Spatial models
• +۴ مورد دیگر

Natalia Bailey is a Senior Lecturer at the Department of Econometrics and Business Statistics at Monash University. She holds a PhD from Queen Mary, University of London, and previously served as a Research Associate at the University of Cambridge. Before joining Monash in 2017, she was a Lecturer at Queen Mary, University of London, and worked in the private sector in London for eight years as an economist/strategist at institutions including Citigroup, Lehman Brothers, and Merrill Lynch. Her research focuses on cross-sectional dependence, factor models, and spatial models, with applications to finance, macroeconomics, and climate change impacts on agriculture. Bailey has contributed to projects like the 'Big Data Analytic Approach to Assessing Impacts of Harmful Temperatures on Wheat Crops in Northern Victoria,' where she collaborated with experts to model agricultural resilience under climate change. Her recent work includes analyzing US house prices using spatial models with heterogeneous coefficients and developing the RMT-based LM test for cross-sectional independence in panel data. Bailey’s research bridges theoretical econometrics with practical applications, addressing issues such as climate change, agricultural productivity, and economic forecasting.

• Statistics
• Machine Learning
• Data Science
• +۳ مورد دیگر

Diego Nascimento is an Assistant Professor in Statistics at NEOMA Business School. His research focuses on statistical modeling, machine learning, spatio-temporal dependencies, and data visualization, with applications in supply chain management, neurosciences, and industrial projects. He has published in top-tier journals like the Journal of the Royal Statistical Society Series C and Pattern Recognition , collaborating with companies in South America and healthcare institutions. His work bridges theoretical statistics with practical industry challenges, emphasizing Bayesian methods and dynamic models. Key research areas include spatio-temporal modeling, neural data analysis, and optimization techniques. Recent studies involve clinical trials on transcranial stimulation effects and predictive analytics for supply chains during the pandemic. He actively contributes to interdisciplinary projects, combining statistical rigor with real-world applications in healthcare and environmental monitoring. Award-winning research includes advancements in imbalanced classification, safety-stock prediction, and entropy analysis in clinical trials. His collaborative projects reflect a commitment to both academic innovation and industrial relevance, with ongoing work in neuroimaging and supply chain resilience.

• Spine Biomechanics
• Back Pain
• Musculoskeletal Conditions
• +۳ مورد دیگر

Alex Breen serves as Visiting Associate Professor at Bournemouth University's Faculty of Science and Technology and full-time Senior Research Fellow/Technology Lead at AECC University College. His research investigates mechanical aggravation of musculoskeletal conditions through quantitative fluoroscopy analysis of spinal motion, with emphasis on lumbar intervertebral dynamics and back pain mechanisms. His educational background includes: PhD in Prosthetics and Biomechanics (Bournemouth University, 2016) MSc in Medical Physics (Open University, 2012) BSc (Hons) in Physics with Medical Applications (Exeter University, 2005) Dr. Breen's research focuses on identifying biomechanical biomarkers for treatment-resistant chronic low back pain through quantitative assessment of intervertebral motion sharing patterns. He examines relationships between disc degeneration, spinal kinematics, and pain using fluoroscopic imaging, finite element modeling, and motion capture systems. Recent work explores microgravity effects on spinal geometry and spatio-temporal clustering of asymptomatic spinal motion. Analysis of his 2021-2025 publications reveals consistent emphasis on methodological validation (e.g., motion capture systems, fluoroscopy), clinical translation of biomechanical findings, and international collaboration in chiropractic research. Key themes include cervical/lumbar motion analysis, disc pressure modeling, and development of patient-specific spinal assessment protocols. His scientific recognition includes: 2019 NCMIC/JMPT RESEARCH AWARD Society for Back Pain Research Travel Fellowship (2016) Dr. Breen supervises PhD candidates Jacqueline Rix (biomechanical effects of spinal manipulation) and Terence McSweeney (quantitative imaging biomarkers). He has secured research funding including the Radiological Research Trust Travel Grant (2016) and serves on the Society for Back Pain Research executive committee (2018-present). His extensive peer review activities span journals including The Spine Journal, BMC Musculoskeletal Disorders, and Frontiers in Sports and Active Living. As AECC University College's Technology Lead, he directs biomechanical research infrastructure development and methodology innovation, particularly in spinal kinematics assessment and clinical translation of engineering approaches to musculoskeletal health.

Lin Linمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Machine Learning
• Blockchain
• +۶ مورد دیگر

Lin Lin is a Senior Lecturer in the Department of Informatics at New Jersey Institute of Technology (NJIT). Her work bridges artificial intelligence, blockchain, and intelligent transportation systems, focusing on novel AI applications across domains. Education: Ph.D. Lin's research spans Artificial Intelligence , Machine Learning , and Blockchain , with notable contributions to traffic signal control, watermarking robustness, and financial modeling. She explores human-AI perception alignment, synthetic data generation for rare events, and deep learning in transportation. Recent publications highlight trends in Generative AI (e.g., RAGIC for stock prediction), Reinforcement Learning in traffic systems (PairUpLight), and GANs for image inpainting. Her work integrates domain knowledge into neural architectures, emphasizing practical real-world applications.

• Econometrics
• Quantitative Methods in Law
• Empirical Legal Studies
• +۳ مورد دیگر

Prof. Philip Hans Franses holds dual professorships at Erasmus University Rotterdam: Full Professor of Applied Econometrics at Erasmus School of Economics and 0.2 FTE Full Professor of Quantitative Methods in Law at Erasmus School of Law. He serves as Vice-Dean for Reputation and Impact at the Law School and previously was Dean of Erasmus School of Economics (2006–2019). His research bridges econometrics and legal studies, focusing on applying quantitative methods to legal issues such as empirical legal studies, economic forecasting, and modeling complex societal problems. He is internationally recognized as the Netherlands' leading econometrician, with contributions to time series analysis, forecasting methodologies, and ethical research practices. Franses has supervised 33 PhD students and teaches minors like 'Quantitative Insight for Lawyers.' His work emphasizes answering practical questions through modern econometric models, with recent studies on Chinese loans in Africa, fashion trends' economic predictions, and maritime risk assessment. Key research areas include econometric modeling, economic growth analysis, and interdisciplinary legal-economics collaborations. He has published extensively on forecasting techniques, bias detection in forecasts, and spatio-temporal clustering. Franses actively contributes to policy debates through media engagements and academic leadership roles, advocating for multidisciplinary approaches to societal challenges.

• Machine Learning
• Dynamical Systems
• Control Systems
• +۴ مورد دیگر

Priyabrata Saha is a Research Fellow at the Georgia Institute of Technology, affiliated with the College of Engineering and the Department of Electrical and Computer Engineering. Research interests include: Deep learning applications in ocean acoustics Control systems for autonomous vehicles Reduced-order modeling of partial differential equations Robust perception in autonomous systems Spatiotemporal dynamics prediction His work spans interdisciplinary domains, combining machine learning with physical modeling for applications in oceanography , robotics , and sensor systems . Key trends in his publications highlight: Integration of physics-based models with generative deep learning Real-time control algorithms for multi-agent systems Resource-efficient architectures for autonomous perception Hybrid methods in dynamical system modeling

Sam Baughمشاهده پروفایل

استادیار

• Spatial Statistics
• Climate Science
• Environmental Statistics
• +۳ مورد دیگر

Sam Baugh is an Assistant Professor of Statistics at Pennsylvania State University's Department of Statistics since Fall 2023. He holds a PhD from UCLA (2022) and MS/BS degrees from the University of Chicago. His research focuses on developing statistical methods for climate change impacts, spatio-temporal modeling, Bayesian hierarchical approaches, and psychometrics, with collaborations in medicine/public health. Education: Ph.D. in Statistics, UCLA (2022) MS in Statistics, University of Chicago (Advisor: Michael Stein) BS in Mathematics, University of Chicago Research interests emphasize climate science applications, including ocean/atmosphere changes and extreme event probabilities. Methodologically, he specializes in: Bayesian hierarchical models Spatio-temporal statistics Computational approximations Psychometric modeling Recent work spans climate attribution studies, medical AI applications, and latent variable modeling. His publications demonstrate cross-disciplinary impact across climate science, surgery outcomes, and educational measurement. Awards include the NSF Postdoctoral Fellowship (2022-2023) and UCLA's Outstanding Ph.D. Student Award (2022). Collaborates with institutions like Lawrence Berkeley National Lab and medical teams in plastic surgery research. Active in both environmental and health-related statistical method development.

Ephraim Hanksمشاهده پروفایل

دانشیار

• Spatio-Temporal Statistics
• Ecology
• Epidemiology
• +۳ مورد دیگر

Ephraim Hanks is an Associate Professor and Chair of Graduate Admissions in the Department of Statistics at Pennsylvania State University. He holds a Ph.D. in Statistics from Colorado State University (2013), an M.S. and B.S. in Mathematics from Utah State University (2010 and 2002). His research focuses on spatio-temporal statistical methods applied to ecology and epidemiology, emphasizing computational and modeling advancements to address scientific questions in these fields. He serves on the executive board of the ASA's Section on Statistics and the Environment and leads Penn State's graduate admissions in statistics. Education: Ph.D. in Statistics, Colorado State University, 2013 M.S. in Statistics, Utah State University, 2010 B.S. in Mathematics, Utah State University, 2002 Research interests include developing statistical models for spatial and spatio-temporal systems, with applications to wildlife movement, disease spread, and environmental monitoring. His work bridges theoretical statistics with practical challenges in ecology and public health. Recent projects address disease spillover dynamics, animal migration patterns, and vaccine allocation strategies during outbreaks. Scientific contributions span epidemiological modeling (e.g., SARS-CoV-2 transmission analysis), ecological connectivity (e.g., landscape genetics of species), and methodological innovations in spatial statistics. His 2017 Early Investigator Award from the ASA highlights his early-career impact in environmental statistics. Teaching includes advanced courses such as Regression Analysis (STAT 511), Design of Experiments (STAT 461), and Stochastic Processes (STAT 416). He is affiliated with the Center for Infectious Disease Dynamics at Penn State, fostering interdisciplinary collaboration on global health challenges. Labs/Teams: Active in the Center for Infectious Disease Dynamics, focusing on statistical approaches to disease ecology and public health interventions.

Julie Vercelloniمشاهده پروفایل

استاد مهمان

• Coral Reef Conservation
• Machine Learning Applications
• Citizen Science
• +۳ مورد دیگر

Dr. Julie Vercelloni is a Visiting Professor at the School of Mathematical Sciences within the Faculty of Science at Queensland University of Technology (QUT). She holds a PhD from QUT and the Australian Institute of Marine Science (AIMS), alongside a MSc from Université Pierre et Marie Curie and a BSc from Université Aix-Marseille II. Her research focuses on integrating advanced technologies like machine learning, virtual reality (VR), and citizen science with statistical methodologies to address challenges in coral reef conservation. Key projects include the Virtual Reef Diver initiative, leveraging citizen science for reef monitoring, and using VR to assess ecological aesthetics. Dr. Vercelloni’s work emphasizes interdisciplinary approaches to understand and mitigate threats to coral reef ecosystems. Her academic qualifications include a PhD in marine science (QUT/AIMS), MSc in applied mathematics (UPMC), and BSc in biology (Aix-Marseille II). She collaborates extensively with institutions like AIMS and the Great Barrier Reef Foundation, contributing to both theoretical and applied conservation research. Publications highlight her expertise in Bayesian statistical methods, ecological data analysis, and the application of AI to environmental monitoring. Projects led by Dr. Vercelloni aim to enhance reef resilience through innovative data integration and community engagement strategies.

• Climate Science
• Carbon Dioxide Removal (CDR)
• Earth System Modeling
• +۳ مورد دیگر

Anusha Sathyanadh is a Research Fellow at the Department of Energy and Process Engineering, Norwegian University of Science and Technology (NTNU), within the Faculty of Engineering. Her current research focuses on ocean-based Negative Emission Technologies (NETs) and their integration with land-based solutions like BECCS to achieve climate neutrality, as part of the EU Horizon OceanNET project. She holds a PhD in Atmospheric and Space Sciences from Savitribai Phule Pune University (2018) and has conducted postdoctoral research at the Swedish University of Agricultural Sciences (SLU). Education: B.Sc. Physics (Calicut University, India), M.Sc. Meteorology (Cochin University of Science and Technology, India). Her PhD work explored monsoon boundary layer regimes and their moisture/energy budgets, contributing to improved understanding of spatiotemporal variations in the region. She has authored over 15 peer-reviewed articles in journals like JGR, Atmospheric Research, and Journal of Hydrology. Research interests span Earth system modeling, carbon cycle interactions, climate mitigation strategies, and monsoon dynamics. Her recent work emphasizes synergistic CDR approaches and their Earth system impacts. She has presented at conferences including the Norwegian Geophysical Society Assembly and NTNU Department Seminars, focusing on CDR efficacy and net-zero pathways.

Laura Luna Castilloمشاهده پروفایل

استادیار

• Digital Art
• Immersive Media
• XR/VR/AR
• +۹ مورد دیگر

Laura Luna Castillo is an Assistant Professor in the Department of Digital Arts and Experimental Media (DXARTS) at the University of Washington. She holds a PhD in DXARTS (2024), an M.A. in Visual Arts from the University of Sussex (2017), and a B.A. in Fine Arts and Interactive Media from Teesside University (2015). Her work bridges multimedia art, technology, and performance, focusing on themes of memory, displacement, and the perception of space through immersive media, VR/AR, and generative processes. Research interests include the intersection of digital technologies with traditional craft, the documentation of domestic spaces through 3D scanning, and the creation of interactive installations that explore human migration and identity. Notable works include The Kaleidoscope of the Eternal Now (2020), awarded first place at Mov en Mov Festival, and Comprehension of Spaces (2019), showcased at Cube Fest. She has been a SHAPE 2016 artist and has collaborated internationally with institutions like EMPAC and Rensselaer Polytechnic Institute. Key awards include recognition at CYNETART, Unsound Krakow, and the Hello World Festival, alongside residencies at Kamiyama, Japan, and the Mexican Consulate in Montreal. Her work frequently combines motors, sensors, and algorithmic systems to create dynamic, audience-responsive environments. Current projects include From habit to in-habit , an expanded theater project exploring migration narratives through virtual doubles, and Production of the Ordinary , a participatory archive of everyday life using mobile 3D scanning.

Tobi Eniolu Morakinyoمشاهده پروفایل

استادیار

• Urban Climatology
• Climate Change and Health
• Sustainable Urban Design
• +۳ مورد دیگر

Dr. Tobi Eniolu Morakinyo is an Assistant Professor at Texas A&M University. He holds a Ph.D. in Urban Climate from the City University of Hong Kong (2013–2016), an M.Tech in Urban Climatology from Federal University of Technology, Akure (Nigeria), and a B.Tech in Meteorology. His research focuses on urban climatology, climate change impacts on health, and nature-based solutions for urban heat adaptation in sub-Saharan Africa. He uses mixed methods like numerical modeling (ENVI-met, WRF), remote sensing, and qualitative surveys. Key research areas include heat-health relationships, green infrastructure effectiveness, and thermal inequalities. He has secured grants as Co-PI/Co-I for projects addressing urban climate adaptation, fostering international collaborations and mentoring graduate students. Awards include a Postdoctoral Fellowship (2016–2019) and multiple academic excellence awards from City University of Hong Kong. His work emphasizes actionable guidelines for heat mitigation using green-blue infrastructure, with a focus on cities like Lagos, Nigeria. Publications span over 30 peer-reviewed articles in journals like Weather and Climate Extremes , Urban Climate , and Building and Environment .

Shafiqul Islamمشاهده پروفایل

استاد

• Water Diplomacy
• Climate and Health
• Remote Sensing
• +۳ مورد دیگر

Shafiqul Islam is a Professor in the Department of Civil and Environmental Engineering and a Professor of Water Diplomacy at the Fletcher School of Law and Diplomacy at Tufts University. He holds the distinction of being the first Bernard M. Gordon Senior Faculty Fellow in Engineering at Tufts. His research focuses on integrating theory and practice to address water-related challenges, including water diplomacy, climate impacts, and flood forecasting. He has held academic positions since 1991, including roles at the University of Cincinnati and leadership roles at Tufts. Education: Sc.D. (MIT, 1991), M.S. (University of Maine, 1987), B.S. (Bangladesh University of Engineering and Technology, 1983). Research interests span water diplomacy, climate resilience, remote sensing, and data-driven decision-making. His work emphasizes actionable outcomes through interdisciplinary collaboration, with projects in Bangladesh, India, and beyond. Notable contributions include flood forecasting systems, national water planning frameworks, and policy advising for multinational organizations. Publications reflect expertise in hydrology, climate science, and policy, with recent trends focusing on extreme weather prediction, transboundary water management, and principled pragmatic frameworks. Awards include Fellow of the American Geophysical Union (2020). Grants and professional activities include leadership in NSF-funded initiatives like the Water Diplomacy Network and the NRT-HDR program. Teaching includes courses on data-driven decision-making, physical hydrology, and engineering diplomacy.