جستجوی استاد راهنمای دانشگاهی

Upaka Rathnayake is a Professor of Civil Engineering and Principal Investigator at the Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE) research unit at Atlantic Technological University Sligo, Ireland. He has held academic and research roles globally, including in Sri Lanka, Japan, the UK, New Zealand, Australia, and Fiji. His research focuses on water resources management, hydrological modeling, climate analysis, and AI-driven solutions for environmental challenges. He holds a PhD from the University of Strathclyde and advanced certifications from Hokkaido University. Education: PhD in Optimal Management of Urban Sewer Systems (University of Strathclyde, 2013) Professional Memberships: Institution of Engineers Sri Lanka, Engineers New Zealand, International Association of Hydrological Sciences Research interests include: Hydrological modeling and climate change adaptation Multi-objective optimization and soft computing techniques Explainable AI applications in environmental systems Remote sensing and GIS for water resource management Recent articles highlight AI-driven solutions for air quality prediction, soil nutrient analysis, and flood risk assessment. Awards include the 2023 Presidential Award for Scientific Publications and multiple university excellence awards. He actively advises PhD students on projects like urban water systems optimization and climatic trends analysis. Rathnayake is an editorial board member of journals like Scientific Reports and PLoS ONE , contributing to peer review and policy-oriented research. His work bridges data-driven methods with traditional hydrological practices to address global environmental challenges.

• Water Resources Management
• Hydrological Modeling
• Climate Analysis
• +۶ مورد دیگر

James Sweeney serves as Professor in the Department of Mathematics and Statistics at the University of Limerick, concurrently holding memberships in the Centre for Battery and Energy Materials Research and the Mathematics Applications Consortium for Science and Industry (MACSI). Actively accepting PhD students, his research bridges theoretical mathematics with practical industry applications across diverse sectors including energy materials, real estate, and public health. His research portfolio demonstrates exceptional interdisciplinary range, with core expertise in machine learning algorithms (particularly time series classification and neural networks), geospatial statistics for property valuation, and epidemiological modeling for disease surveillance. Key methodological contributions include evolutionary algorithms for optimization, dissimilarity-preserving representation learning, and flexible geospatial smoothing techniques that address complex real-world data challenges. Analysis of his 23 publications (2015-2024) reveals accelerating scholarly output since 2020, with 2024 being particularly prolific. His work consistently targets high-impact applications: developing diagnostic thresholds for bovine tuberculosis, modeling COVID-19 transmission dynamics in Dublin, and creating neural network solutions for geodemographic clustering. This trajectory reflects deepening engagement with computational approaches to solve pressing societal problems through mathematical innovation. As a PhD supervisor, he cultivates next-generation researchers in advanced computational methods. His collaborative framework extends through MACSI's industry partnerships and the Centre for Battery and Energy Materials Research, where mathematical modeling directly informs energy technology development. These dual affiliations position him at the critical intersection of academic research and industrial application, particularly in Ireland's growing tech and energy sectors. His laboratory activities center around computational mathematics teams within MACSI, focusing on applying statistical learning to battery materials research and real-world data challenges. Current projects involve time series analysis for sensor data, geospatial modeling for economic forecasting, and optimization algorithms for veterinary epidemiology – demonstrating remarkable methodological versatility across traditionally disparate domains.

• Machine Learning
• Time Series Analysis
• Geospatial Statistics
• +۳ مورد دیگر

Dr. Gavin McArdle is an Associate Professor at the University College Dublin (UCD) School of Computer Science, specializing in spatial data analysis and smart cities. He holds academic affiliations with the National Centre for Geocomputation (Maynooth University) and CeADAR (Data Analytics Centre). His research focuses on urban dynamics, geovisual analytics, smart transportation, and remote sensing applications. He has received a College of Science Teaching Excellence Award for his contributions to education. McArdle earned his BSc, PhD, and a Prof Dip in University Teaching & Learning from UCD. His work bridges academia and industry through collaborative grants, including those from Science Foundation Ireland and EU funding. Notable projects include the Dublin Dashboard (urban analytics platform) and DubSim (traffic simulation using digital footprints). His research outputs span over 147 publications, with recent work addressing Airbnb's impact on urban gentrification, sustainable mobility, and environmental monitoring via satellite data. He actively contributes to professional committees, including roles in the UCD Data Protection Impact Assessment Committee and international conferences like Web and Wireless GIS. McArdle coordinates courses such as Research Practicum and Computer Programming II, emphasizing practical research and technical skills. His interdisciplinary approach integrates machine learning, spatial statistics, and urban informatics to address real-world challenges in smart cities and environmental sustainability.

• Smart Cities
• Geovisual Analysis
• Urban Dynamics
• +۵ مورد دیگر

Dr. Salem S. Gharbia is the Head of the Department of Environmental Science and a Principal Investigator at Atlantic Technological University (ATU). He leads the Centre for Environmental Research Innovation and Sustainability (CERIS) and co-founded the Centre for Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE). His research focuses on climate resilience, environmental monitoring, and modeling, with expertise in Geographic Information Systems (GIS), wireless sensor networks, and climate change impacts. Dr. Gharbia coordinates major EU projects like Horizon 2020 SCORE and has secured over €14M in research funding. He holds a PhD in Environmental Engineering from Trinity College Dublin, where he received the prestigious Ussher Award. His work spans collaborations with the Irish EPA, Horizon Europe, and the Marine Institute, addressing coastal flooding, microplastic detection, and sustainable agriculture. Education: PhD in Environmental Engineering, Trinity College Dublin. Research interests include climate adaptation strategies, urban resilience, and innovative sensor technologies for environmental monitoring. His projects emphasize interdisciplinary approaches to address global challenges such as rising sea levels, extreme rainfall, and coastal erosion. Awards: Trinity College Ussher Award. Grants: Over €14M secured over five years for projects like EmpowerUS, Pro-climate, and WaterFutures. Advising: Accepting PhD students in environmental science and engineering. Labs: CERIS and MISHE, focusing on climate modeling and environmental systems.

• Climate Resilience
• Environmental Monitoring
• Environmental Modeling
• +۳ مورد دیگر

Prof. Gregorio Iglesias is a Professor of Marine Renewable Energy at University College Cork (UCC) and Honorary Professor of Coastal Engineering at the University of Plymouth. His expertise lies in Marine Renewable Energy and Coastal Engineering, with a focus on wave and tidal energy systems, offshore wind integration, and coastal protection strategies. He has secured over €12M in research funding as Principal Investigator and authored/edited key texts such as Wave and Tidal Energy (Wiley) and Ocean Energy and Coastal Protection (Springer). Education: BEng (Civil Engineering, 1992), MEng (Civil Engineering, 1993), PhD (Engineering, 2001). Research Interests: Advanced modeling of wave energy converters, floating offshore wind turbines, coastal erosion mitigation, and climate change impacts on marine energy resources. His work bridges theoretical advancements and practical applications, including coasts like the Port of Gijón (Spain) and the Shannon Estuary. Recent publications highlight climate-driven renewable energy transitions, multi-hazard coastal resilience frameworks, and techno-economic assessments of offshore systems. He chairs the IEC Standards panel for wave energy device testing and serves as Subject Editor for Energy (Elsevier) . Professional Activities: Lead of Marine Renewable Energy research at MaREI (Ireland), former Head of the COAST Engineering Group at Plymouth (2012–2018), and member of PIANC’s Universities Consortium. His work has generated 5,459 citations with an h-index of 41. Teaching: Delivers modules on Ocean Energy (NE4003/NE6005) and Hydraulics (CE3007).

• Marine Renewable Energy
• Coastal Engineering
• Wave Energy Conversion
• +۵ مورد دیگر

Lars Pforte is a Lecturer in the Faculty of Science & Engineering at Maynooth University, affiliated with the Mathematics and Statistics department. He holds a PhD in Mathematics and a Masters Degree in Geocomputation. PhD in Mathematics Masters in Geocomputation His research spans both pure mathematics and applied geospatial analysis. Key areas include: Representation theory of finite groups Urban airspace traffic management (UTM) Road safety analysis Data imputation in space-time series While his recent publications focus on algebraic structures like symplectic modules for the Klein-four group and permutation module vertices, he also applies Bayesian statistical methods to urban analytics and transportation safety. No scientific awards are explicitly mentioned in the available information.

• Representation Theory
• Finite Groups
• Geocomputation
• +۳ مورد دیگر

Christopher Brunsdon is Professor of Geocomputation and Director of the National Centre for Geocomputation at Maynooth University's Faculty of Social Sciences. Previously, he held positions at the University of Liverpool, Leicester, Glamorgan, and Newcastle. His academic credentials include a BSc in Mathematics from Durham University and an MSc in Medical Statistics and PhD in Geography from Newcastle University. Research interests focus on spatial statistics, data science, and spatial analysis, with emphasis on open-source software (especially R) and reproducible methods. Applied domains include crime pattern analysis, health geography, and environmental applications. Current projects include 'Mapping Lineages: Quantifying the Evolution of Maps of the British Isles' and 'Building city dashboards'. Brunsdon's recent publications (2018-2020) demonstrate strong methodological contributions to geocomputation, spatial regression, and geodemographics. Trends include reproducibility in spatial science, multiscale modeling, and applications in health geography and urban analytics. He leads the National Centre for Geocomputation, fostering innovation in spatial data science. Grant leadership includes an ERC Advanced Grant (RIGAR) and industry collaborations like consultancy for SiteZeus.

• Spatial Statistics
• Data Science
• Spatial Analysis
• +۳ مورد دیگر

Joseph Timoney is a professor at the Department of Computer Science , Maynooth International Engineering College , Maynooth University. He teaches undergraduate programs in Computer Science and Music Technology, with expertise in audio signal processing, musical sound synthesis, and digital modeling of analog subtractive synthesis. His research spans sound synthesis algorithms, audio watermarking, and ubiquitous music ecosystems.

• Audio Signal Processing
• Musical Sound Synthesis
• Digital Audio Watermarking
• +۳ مورد دیگر

Viet Quoc Pham is an Assistant Professor in Networks and Distributed Systems at Trinity College Dublin's School of Computer Science and Statistics and a CONNECT Associate Investigator. His research integrates convex optimization, game theory, and machine learning to advance edge computing, wireless AI, and next-generation networking for 6G, IoT, and blockchain applications. Education: PhD in Telecommunications Engineering, Inje University, Korea (2017) His work centers on three interconnected thrusts: (1) Computing innovations in edge AI, aerial computing, and edge of things; (2) Intelligence through wireless AI and federated learning; and (3) Networking advancements in 6G, IoT, intelligent surfaces, metaverse, and blockchain. This cross-disciplinary approach optimizes cloud-edge systems and wireless infrastructure using mathematical frameworks. Recent publications (2021-2024) demonstrate applied impact across security (smart speaker intrusion detection), environmental science (satellite carbon monitoring), healthcare (mental disorder detection), and e-commerce (basket recommendation systems), reflecting his methodology of adapting AI/optimization to domain-specific challenges. Scientific Awards: Korea NRF funding for outstanding young researchers (2019-2024) Best Ph.D. Dissertation Award, Inje University (2017) Top Reviewer Award, IEEE Transactions on Vehicular Technology (2020) Golden Globe Award, Vietnam Ministry of Science (2021) IEEE ATC Best Paper Award (2022) Enterprise Ireland Coordination Support Award (2023) Dr. Pham secured competitive funding including Korea NRF and Enterprise Ireland grants. As Editor for Journal of Network and Computer Applications and Scientific Reports, and Lead/Guest Editor for IEEE Internet of Things Journal, IEEE Transactions on Consumer Electronics, and Computer Communications, he shapes discourse in networking and computer systems through rigorous peer review and special issues. Through the CONNECT Centre, he collaborates with industry partners on Ireland's national research initiative for future networks, focusing on practical implementations of 6G architectures, IoT security protocols, and edge AI frameworks for real-world deployment.

• Edge Computing
• Edge AI
• Aerial Computing
• +۱۱ مورد دیگر

Dr. Stig Hellebust is a Lecturer in Physical Chemistry at the School of Chemistry, University College Cork (UCC), Ireland. Based in Room 206B of the Kane Building, he can be contacted at s.hellebust@ucc.ie or +353 214902680. His research focuses on atmospheric chemistry, environmental monitoring, and advanced data analysis techniques for understanding air quality and pollution sources across Ireland. Dr. Hellebust's research interests span several key areas of environmental chemistry and data science: Atmospheric observational data analysis, particularly high-dimensional datasets collected over extended time periods Application of multivariate statistical methods and machine learning for environmental data interpretation Source apportionment of atmospheric pollutants using receptor modeling techniques Development of algorithms for processing large environmental datasets Application of clustering and classification techniques to identify pollution sources Fourier-transform infrared spectroscopy data analysis His extensive publication record demonstrates expertise in air quality monitoring, particularly focusing on PM2.5 sources, urban pollution dynamics, and health impacts. He frequently employs advanced statistical methods including principal component analysis (PCA), positive matrix factorization (PMF), and various machine learning approaches to extract meaningful information from complex environmental datasets. His work bridges atmospheric science, public health, and data analytics, with significant contributions to understanding Ireland's air quality challenges. Dr. Hellebust has secured substantial research funding from multiple sources including the Environmental Protection Agency (EPA), Health Research Board, Science Foundation Ireland, and European Union programs. His current major projects include "Sources of PM2.5 in the Air of Irish Towns" (2024-2027, €233,796.00) and "Impact of Agricultural Emissions on Rural and Urban Air Quality" (2022-2025, €119,700.00), demonstrating his leadership in addressing critical environmental challenges. He currently supervises doctoral student Rósín Eileen Byrne and has previously supervised Eimear Heffernan who completed her PhD in 2022 on "Spatial and temporal variation of ambient carbonaceous aerosol in Ireland and strategies for effective monitoring of source contributions." His mentorship extends to interdisciplinary research connecting chemistry, environmental science, and public health. Dr. Hellebust is an active member of UCC's Atmospheric and Environmental Chemistry research group, collaborating with colleagues across Ireland and internationally on air quality monitoring and pollution source identification projects. His work has significant policy implications for urban planning, public health interventions, and environmental regulation in Ireland and beyond.

• Atmospheric Chemistry
• Environmental Chemistry
• Air Quality
• +۵ مورد دیگر

Dr. Damien Dupré is an Assistant Professor of Business Research Methods at Dublin City University's Business School. He holds a Ph.D. in Social and Experimental Psychology from Université Grenoble-Alpes, France. His research focuses on psycho-physiological responses in real-world settings, particularly through the analysis of facial expressions and wearable device data. He co-developed the DynEmo database for dynamic facial emotion analysis and collaborated with institutions like Queen’s University, Sensum Ltd, and UCD’s Insight Centre. His expertise includes multivariate time series analysis for machine learning applications in emotion recognition and human-computer interaction. Education: Ph.D. in Social and Experimental Psychology (Université Grenoble-Alpes), postdoctoral work involving physiological measurements of marathon runners. Key collaborations include projects with Sensum Ltd (emotion sensors), Queen’s University (facial expression analysis), and Ixiade (emotional UX evaluation). Research interests span emotion statistics, wearable devices, and physiological computing. Recent work emphasizes automatic facial expression recognition systems and their validation through dynamic datasets. His publications address challenges in emotion detection accuracy across commercial classifiers and the impact of facial interface designs on emotional perception. Teaching responsibilities include Data Analytics for Business, Quantitative Research Methods, and Strategic Consultancy modules. He leads the DCU R Stats Club and actively contributes to open-source tools for data science education. Current projects include the Motoklik–AI-PoC initiative as DCU PI. Professional engagement includes Mastodon activity promoting RStats pedagogy and GitHub repositories showcasing code for emotion analysis (e.g., machine_challenge repo). His work bridges psychological theory, technological innovation, and business analytics applications.

• Emotion Recognition
• Facial Expressions
• Wearable Devices
• +۳ مورد دیگر

Alexey Lastovetsky is an Associate Professor at the School of Computer Science, University College Dublin (UCD), where he is the founding Director of the Heterogeneous Computing Laboratory (HCL). He holds a PhD from the Moscow Aviation Institute and a Doctor of Science (Habilitation) from the Russian Academy of Sciences. His research focuses on high-performance heterogeneous computing, energy-efficient computing, and parallel algorithms for modern architectures. He has published over 175 peer-reviewed papers and authored influential monographs in the field. Education: PhD (Moscow Aviation Institute), Doctor of Science (Russian Academy of Sciences) Affiliations: UCD since 2001; previously Senior Scientist at Lomonosov Moscow State University (1989–1994) and Principal Scientist at the Russian Academy of Sciences (1995–1999) His research interests span heterogeneous computing , energy-efficient systems , and high-performance parallel algorithms . He has developed novel methodologies for workload distribution optimization, energy modeling, and communication performance analysis. His work on the OpenH programming model and SUARA communication algorithm exemplifies his contributions to scalable parallel computing. He has secured over €4.5M in grants , including four prestigious SFI Investigator awards. His recognition includes being ranked in the Stanford/Elsevier Top 2% Scientists list since 2020 and a ScholarGPS Highly Ranked Scholar distinction. He has organized over 300 international conferences and serves on editorial boards of journals like Journal of Parallel and Distributed Computing . Teaching responsibilities include coordinating modules on High-Performance Computing , Parallel Computing , and UNIX Programming . His lab, HCL, is a global leader in heterogeneous computing research, advancing energy-efficient and scalable solutions for modern HPC platforms.

• High Performance Heterogeneous Computing
• Energy Efficient Computing
• Parallel Computing
• +۴ مورد دیگر

Dr. Aoife Donnelly serves as a Lecturer in the School of Food Science and Environmental Health at Technological University Dublin (TU Dublin), teaching environmental sciences, protection policy, and health impacts since 2016. Her academic foundation includes a Ph.D. in Engineering from Trinity College Dublin focused on Irish air pollution modeling, followed by industry experience as an Environmental Analyst specializing in emissions control and an EPA fellowship-funded postdoctoral position developing Ireland's national air quality forecast model. Her transdisciplinary research applies spatio-temporal statistical and deterministic modeling to environmental health challenges, with core expertise in air pollution forecasting, anthropogenic emissions analysis, and fungal spore concentration modeling. She pioneered investigations into population health benefits from blue and green exercise, sustainable transportation, citizen science engagement, and pro-environmental behavior change. Her methodological innovations bridge environmental science with public health outcomes through evidence-based intervention design. Analysis of her 2011-2019 publications reveals three dominant research trajectories: advanced air quality modeling techniques for Ireland (accounting for 70% of output), health impact assessments of environmental factors (20%), and interdisciplinary studies on nature-human interactions (10%). This progression demonstrates increasing integration of environmental engineering with behavioral health sciences, particularly in quantifying reciprocal benefits of human-nature engagement. Scientific recognition includes: EPA fellowship for postdoctoral air quality model development Dr. Donnelly's collaborative work spans environmental agencies, public health institutions, and sports science researchers, evidenced by co-authorship with Trinity College Dublin's Broderick and Misstear on atmospheric studies and MacIntyre on green exercise projects. Her research has secured funding through Ireland's Environmental Protection Agency for air quality forecasting systems and citizen science initiatives investigating sustainable physical activity. She maintains active partnerships with Ireland's environmental monitoring networks and international green exercise research consortia, directing projects that combine air pollution data with behavioral health metrics to inform urban planning and public health policy.

• Air Quality Modelling
• Environmental Health
• Spatio-temporal Statistical Modelling
• +۷ مورد دیگر

Dr. Adrian O'Hagan is a Lecturer in Statistics and Actuarial Science at University College Dublin (UCD) School of Mathematics and Statistics, with a focus on machine learning and statistical modeling. He completed his PhD in Statistics at UCD in 2012 and holds an MSc in Statistics from UCD (2006). As a funded investigator at the Insight Centre, his work bridges computational statistics with practical applications in insurance, healthcare, and manufacturing. Education: PhD Statistics, UCD (2012) MSc Statistics, UCD (2006) Bachelor of Actuarial and Financial Studies, UCD Research Interests span machine learning, Bayesian inference, network analysis, and actuarial science. His recent work includes: Developing probabilistic models for network analysis and EHR-based phenotyping Advancing clustering algorithms with uncertainty quantification and optimization Applying statistical methods to insurance risk, manufacturing analytics, and data compression Publications highlight his expertise in variational Bayes, Gaussian mixtures, and multivariate claim modeling, with interdisciplinary impacts in healthcare and finance. He collaborates on real-world data analysis and contributes to open-source actuarial tools like mvClaim .

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

Rachel Murphy is a Lecturer in the School of History and Geography at the University of Limerick since 2018, specializing in Irish history and digital humanities. She concurrently serves as Editorial and Mapping Assistant for the Royal Irish Academy's Irish Historic Towns Atlas program. Her academic roles include chairing the Irish Historic Towns Atlas Digital Working Group and membership on the National Library of Ireland's Genealogy and Heraldry committee. Education includes a PhD in History and Digital Humanities from University College Cork (2017), MA in History of Family from University of Limerick (2008), and BA from University of Oxford (1992). She holds a Higher Diploma in GIS from UCC and a Grad. Dip. Teaching, Learning and Scholarship from UL (2020). Research focuses on landholding history, urban history, family history, and digital tools like GIS. Notable projects include the 'Death and Burial Data: Ireland 1864-1922' (2020-2023) and 'Deep Maps: West Cork Coastal Cultures' (funded by IRC). She emphasizes interdisciplinary approaches, collaborating with computer scientists on data modeling and transcribathon initiatives. Teaching contributions include supervising 37 MA dissertations (2018-2024), directing the MA History of Family program, and lecturing in Irish history. Awards include 2023 UL Team Teaching Award and AHSS Award for collaborative pedagogy. She has held roles in international business prior to academia, including at eBay Ireland and Accenture. Publications span historical demography, digital humanities methodologies, and Irish social history. Current research explores intersections between historical data curation and emerging technologies, with a focus on open educational resources (OER) development.

• History of Landholding
• Urban History
• Family History
• +۷ مورد دیگر