جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Constraint Programming
• Optimization
• +۴ مورد دیگر

Professor Ken Brown is a faculty member at the Department of Computer Science, University College Cork (UCC), Ireland. He holds roles as Professor and Deputy Director of the Insight Centre for Data Analytics. His research focuses on Artificial Intelligence, constraint programming, optimization, and applications in wireless/sensor networks. He has led major projects including the Insight Centre (SFI), CTVR (telecom), and Authentic (energy management). Affiliations: Insight Centre, CTVR, GLACIATION, SEISMEC Key awards: IEEE SECON 2015 Best Demo, TAOS 2014 Best Paper Education: BSc (Mathematics, Glasgow), MSc (Logic & Computation, Manchester), PhD (AI in Engineering, Bristol). Extensive postdoc and academic roles at UCC, Aberdeen, and Carnegie Mellon. Research interests include constraint-based decision support, smart building systems, and network resilience. Over 150+ publications in journals like Ad Hoc Networks , Constraints , and conferences like IEEE SECON, ICTAI. Grants: Over €10M secured, including SFI, EI, and ERC funding. Supervised 30+ PhD/MSc students. Current research includes smart energy systems, autonomous network repair, and AI for emergency response.

• Structural Dynamics
• Traffic Loading
• Bridge Loading
• +۷ مورد دیگر

Arturo Gonzalez is an Associate Professor at the School of Civil Engineering, University College Dublin (UCD). He specializes in structural dynamics, bridge loading, and structural health monitoring. His research focuses on bridge assessment, traffic loading effects, and innovative technologies for infrastructure safety. Gonzalez holds a PhD from Trinity College Dublin and has held academic positions at UCD since 2003, including roles as Programme Director for Structural Engineering programs. His work includes over 200 technical publications and significant grant funding exceeding €2 million. Notable contributions include leadership in EU projects like the TRUSS Marie Skłodowska-Curie ITN and the MARS-Fly R&D partnership. Awards include a Teaching Excellence Award (2017) and recognition for EU research leadership (2017). Education: Bachelor's in Civil Engineering (University of Cantabria, Spain, 1995) MSc and PhD in Civil Engineering (Trinity College Dublin, 1996 and 2000) Postgraduate Diploma in University Teaching & Learning (UCD, 2015) Research Interests: His work spans bridge dynamics, traffic-induced structural responses, and educational technology. Key areas include drive-by monitoring for infrastructure assessment, probabilistic maintenance optimization, and fatigue analysis of marine structures. Awards & Grants: Recipient of multiple best paper awards and grants including €3.7M for TRUSS (2015–2018) and €1.7M for MARS-Fly (2017–2021). He chairs international conferences and serves on editorial boards for journals like Structure and Infrastructure Engineering . Teaching & Leadership: Developed hybrid academic advising models and led curricular reforms. Supervised 11 PhD and 7 MEngSc theses. Holds leadership roles in UCD’s Engineering programs and professional networks like the International Association for Life-Cycle Civil Engineering (IALCCE). Labs & Collaborations: Affiliated with UCD’s Transport Research Hub and collaborates internationally on projects involving universities, industry partners (e.g., Arup, Volvo), and research institutes.

• Additive Manufacturing
• Polypropylene
• Heat Transfer Analysis
• +۶ مورد دیگر

David Tormey is a Senior Lecturer and Director of the Precision Engineering Materials and Manufacturing Research Centre (PEM Research Centre) at Atlantic Technological University's Department of Mechanical & Manufacturing Engineering. His research focuses on additive manufacturing, heat transfer optimization, and advanced materials processing, particularly in polypropylene and stainless steel applications. He leads interdisciplinary projects addressing sustainable manufacturing and industrial innovation. Research interests include additive manufacturing techniques, laser welding of polymers, computational fluid dynamics (CFD), and sensor integration for real-time process monitoring. His work contributes to UN Sustainable Development Goals related to Industry, Innovation, and Infrastructure (SDG 9) and Climate Action (SDG 13). Recent studies emphasize roughness effects on heat transfer in additive-manufactured channels, optimization of injection molding processes, and biomedical applications of nanocoatings. Collaborations span academic and industrial partners globally, addressing challenges in energy-efficient manufacturing and materials science. The PEM Research Centre, under his leadership, develops cutting-edge solutions for precision engineering and advanced manufacturing systems. His publications (58+ articles) highlight contributions to thermal engineering, polymer processing, and AI-driven quality control in manufacturing.

Jason Chanمشاهده پروفایل

استاد

• Multisensory Integration
• Cognitive Neuroscience
• Autism Spectrum Disorder
• +۳ مورد دیگر

Jason Chan is a Professor in the Department of Applied Psychology at University College Cork (UCC), Ireland, where he leads research at the intersection of brain and behavior. His work utilizes advanced neuroimaging techniques including magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI), and electroencephalography (EEG) to investigate multisensory integration and its applications in understanding neurological conditions. Dr. Chan earned his BA from California State University, Los Angeles, followed by a D.Phil in Experimental Psychology from the University of Oxford. Prior to joining UCC, he conducted post-doctoral research at Trinity College Dublin and Goethe University, gaining expertise in diverse research methodologies across international institutions. His primary research focus centers on multisensory integration (MSI), examining how perceptual training affects cortical connectivity and how these processes serve as biomarkers for neurological conditions including autism spectrum disorder and mild cognitive impairment in aging populations. Through seemingly simple behavioral tasks coupled with sophisticated neuroimaging, Chan's work provides critical insights into human perception and disorders. Analysis of his recent publications reveals a consistent trajectory in multisensory research, with increasing focus on aging populations, autism spectrum disorders, and the application of predictive coding frameworks to understand perceptual processing differences. His work spans both theoretical neuroscience and practical applications for cognitive rehabilitation. Dr. Chan has secured multiple research grants, including funding from Enterprise Ireland, HEA COVID Support, and the Health Research Board for projects examining fear of falling detection systems, community walking programs for older women, and the impact of chaotic home environments on emotional perception in autism. He actively contributes to the academic community through committee service on the Applied Psychology Ethics, Research, and Teaching Committees at UCC. His professional affiliations include the Federation of European Neuroscience Societies, American Association for the Advancement of Science, Society for Neuroscience, Neuroscience Ireland, and the Association for Psychological Science. Dr. Chan directs the Acme Lab (www.acmelab.science), which serves as the hub for his research team's investigations into brain-behavior relationships, providing a collaborative environment for advanced neuroimaging studies and perceptual research.

Niamh Cahillمشاهده پروفایل

استاد

• Statistical modeling
• Climate change
• Sea-level change
• +۱۰ مورد دیگر

Niamh Cahill is a Professor in the Department of Mathematics and Statistics within the Faculty of Science & Engineering at Maynooth University. Her academic work spans environmental statistics and public health, with a particular focus on developing statistical models to address societal and environmental concerns. She is affiliated with both the Hamilton Institute and ICARUS (the Maynooth University Climate and Environmental Change Research Centre), reflecting the interdisciplinary nature of her research. Dr. Cahill holds a BSc in Chemistry and Statistics from Maynooth University, followed by an MSc and PhD in Statistics from University College Dublin. Prior to joining Maynooth University, she served as a Lecturer/Assistant Professor at University College Dublin (2017-2023) and completed a postdoctoral research associate position at UMASS Amherst (2016-2017). Her research ethos centers on developing statistical models to address societal and environmental concerns. One major research focus involves creating statistical models to assess and interpret indicators of climate change, particularly sea-level change and sea-level extremes. Her work explores and quantifies the spatial non-uniformity and uncertain magnitude of current and future sea-level rise, which aids coastal risk-management decision makers in developing mitigation and adaptation strategies. Another significant research area involves the statistical analysis of population-level health trends, with particular attention to family-planning indicators at national and sub-national levels, especially in the world's poorest countries. This work assesses progress toward meeting Sustainable Development Goals related to health (Goal 3) and gender equality. Dr. Cahill employs a Bayesian approach to statistical modeling, which is particularly suitable for developing complex hierarchical models, accounting for uncertainties related to model parameters, incorporating prior knowledge, and sharing information across data populations. Her recent publications reveal a consistent focus on sea-level reconstruction, climate change indicators, and family planning statistics, demonstrating the dual environmental and public health applications of her statistical methodology. Dr. Cahill has secured significant research funding, including as Principal Investigator for the "Predicting Sea Levels and Sea Level Extremes for Ireland" project (€258,529, 2021-2024) and as Co-PI for several other substantial projects including HydroDare and IHRN. Her research team includes postdoctoral fellows such as Fernando Mayer working on sea-level estimation projects. Within the university community, Dr. Cahill serves on multiple committees including the Academic Council, Faculty of Science and Engineering EDI Committee, and the Department of Mathematics and Statistics PR Committee. She has also held leadership positions such as Outreach Officer for Y-ISA (2021-2022). Dr. Cahill teaches several courses at Maynooth University including DS152 Introduction to Data Science, ST405 Bayesian Data Analysis, ST201 Data Analysis, ST466 Advanced Statistical Modelling, and DS151 Introduction to Data Science, reflecting her expertise in statistical methodology and data science applications.

• Latent Variable Models
• Mixture Models
• Rank Data Models
• +۷ مورد دیگر

Claire Gormley is an Associate Professor of Statistics at University College Dublin (UCD) and a Funded Investigator at the Insight Centre for Data Analytics. She joined UCD in 2006 as an Assistant Lecturer, was promoted to Assistant Professor in 2008, and to Associate Professor in 2017. Her research group specializes in Machine Learning & Statistics with applications spanning genetics, agriculture, and medical sciences. Education PhD in Statistics, Trinity College Dublin (2007) Visiting Scholar, Department of Statistics/Centre for Statistics and the Social Sciences, University of Washington Seattle (2006) Research Expertise Professor Gormley develops advanced statistical methodologies including latent variable models, mixture models, and Bayesian approaches for high-dimensional data analysis. Her work addresses dimensionality challenges in diverse fields such as metabolomics, orthopaedics, and social science, with current projects focusing on model-based clustering for mixed-type high-dimensional datasets. Methodological innovations are consistently applied to real-world problems involving large-scale biological and agricultural data. Publication Trends Her recent publications (2023-2025) demonstrate strong interdisciplinary impact across genetics (tuberculosis, dairy cattle), agricultural science (nitrogen utilization), and medical research (neonatal sepsis). Methodologically, she pioneers mixture models and latent variable frameworks for complex data structures, particularly in multi-omics integration and network analysis. A clear trajectory shows increasing focus on computationally intensive solutions for biological big data, with applications directly addressing food security and healthcare challenges. Research Leadership As a Funded Investigator at the Insight Centre, Dr. Gormley leads a dynamic research group securing competitive grants for interdisciplinary projects. Her team collaborates with veterinary scientists, geneticists, and medical researchers on grant-funded initiatives including tuberculosis genomics and metabolomics data analysis. The group maintains strong industry partnerships in agricultural technology and healthcare analytics, with recent projects developing predictive models for dairy cattle health monitoring and clinical diagnostics.

• Machine Learning
• Statistics
• Actuarial Science
• +۳ 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 .

• Mechanical Engineering
• Materials Science
• Uncertainty Quantification
• +۵ مورد دیگر

Dr. Anton van Beek is an Assistant Professor in the School of Mechanical and Materials Engineering at University College Dublin. He holds a B.S. from HZ University of Applied Sciences (2013), an M.S. from the University of Michigan-Shanghai Jiao Tong University Joint Institute (2017), and a Ph.D. from Northwestern University (2021). His research focuses on integrating domain knowledge with data-driven methods to address uncertainties in complex system design. Notable areas include uncertainty quantification, Bayesian optimization, metamaterials, and digital twins. He leads the ODDS-Lab and teaches modules such as Automotive Vehicle Dynamics, Mechanics of Fluids, and Applied Dynamics. His recent work emphasizes sustainable materials, multiscale modeling, and AI-driven system design. Education: B.S., Mechanical Engineering, HZ University of Applied Sciences (2013) M.S., Mechanical Engineering, UM-SJTU Joint Institute (2017) Ph.D., Mechanical Engineering, Northwestern University (2021) Research Interests: Data-driven design under uncertainty Metamaterials and multiscale systems Bayesian methods and optimization Applications in sustainable materials and digital twins Teaching: Coordinated modules at UCD, Chang’an-Dublin International College, and Shanghai Ocean University Focus on engineering design, dynamics, and optimization

• Marine Geosciences
• Glacial Geomorphology
• Ice Sheet Dynamics
• +۳ مورد دیگر

Dr. Sara Benetti is a Visiting Associate Professor at University College Dublin's School of Earth Sciences and Senior Lecturer in Environmental Change at Ulster University. She specializes in marine geosciences, with expertise in glacial geomorphology, ice sheet dynamics, and submarine geohazards. Her research focuses on reconstructing the extent and behavior of the British-Irish Ice Sheet (BIIS), particularly through geophysical and sedimentological analyses. She has led over ten research cruises and secured funding from NERC, the EU, and Irish government initiatives, including the BRITICE-CHRONO project. Dr. Benetti also evaluates proposals for European and Italian research programs and is a Senior Fellow of the Higher Education Academy. Her work integrates field studies, marine geophysical surveys, and sediment core analyses to understand ice sheet retreat mechanisms, such as those influencing the Malin Sea and Celtic Sea regions. Key contributions include refining deglaciation timelines and documenting the role of meltwater systems and calving events in ice dynamics. She has collaborated with institutions like the National Oceanography Centre, Woods Hole Oceanographic Institution, and the British Antarctic Survey. Dr. Benetti’s research outputs emphasize the Atlantic continental shelf’s geomorphology, submarine landforms, and the interplay between glacial processes and marine environments. Recent studies highlight early BIIS deglaciation driven by glacio-isostatic effects and high relative sea levels. Her articles frequently address ice stream behavior, grounding line dynamics, and subglacial hydrology, supported by multidisciplinary datasets including radiocarbon dating and cosmogenic nuclides. As an educator, she pioneered the BSc in Marine Science and MSc in Remote Sensing and GIS at Ulster University, securing £1.2M for spatial data analytics initiatives. Her grants include leadership roles in projects like BRITICE-CHRONO, advancing understanding of ice sheet decay and climate impacts.

• Transport Network Resilience
• Civil Engineering
• Probability Analysis
• +۷ مورد دیگر

Beatriz Martinez-Pastor is an Assistant Professor in the School of Civil Engineering at University College Dublin (UCD). Her roles include teaching and coordinating modules such as Transport Modelling, Transportation Engineering, and Civil Engineering Design Graphics. She holds a PhD from Trinity College Dublin and an MSc from the University of Cantabria, complemented by a Professional Certificate in University Teaching and Learning from UCD. Her research focuses on transport network resilience, particularly in quantifying system behavior under disruptions like natural disasters and cyber-physical attacks. Key areas include probabilistic analysis, data-driven modeling, and infrastructure vulnerability assessment. She has contributed to frameworks for evacuation planning, cyber-physical system robustness, and flood adaptation strategies. Her articles highlight advancements in accident analysis methods, cyber-physical resilience, and multi-objective optimization for disaster scenarios. Notable grants include the Horizon Europe-funded SETO project (2023–2026) and CAPABLE (2023–2024), addressing transport enforcement and community resilience. Martinez-Pastor has received the Excellence Award (2019) and serves on committees like the TRB Committee on Critical Infrastructures. Her work bridges academic research with practical applications in disaster management, cybersecurity, and sustainable infrastructure.

• Neolithic and Bronze Age Archaeology
• Archaeological Material Culture Studies
• Radiocarbon Dating
• +۳ مورد دیگر

Neil Carlin is an Associate Professor in the School of Archaeology at University College Dublin (UCD). His academic roles include serving as Head of Teaching & Learning (2020–2023) and a member of the Teaching & Learning Committee in the College of Social Sciences & Law. He holds a B.A. in Philosophy from UCD (2001), a M.A. in Archaeology from Queen's University Belfast (2005), and a Ph.D. in Archaeology from UCD (2011). He completed an IRC-funded postdoctoral fellowship (2012–2014) studying Grooved Ware in Ireland. Carlin's research focuses on Neolithic and Bronze Age Ireland and Britain, emphasizing social practices, material culture, and chronology. His projects include the 'Project Radiocarbon' (2021–2024), creating a transnational radiocarbon database, and 'TIME' (2020–2024), examining social change in prehistoric Britain and Ireland. His work challenges traditional narratives, advocating for interdisciplinary approaches and critical theory. His articles address topics like kinship through genetic and archaeological evidence, radiocarbon big data, and Neolithic burial practices. Awards include the R.M. Baguley Award (2018) for best Proceedings of the Prehistoric Society paper and UCD Teaching Excellence Award (2017). Carlin teaches modules on Irish archaeology, archaeological theory, and cultural heritage, emphasizing active learning and critical thinking.

Emma Finlayمشاهده پروفایل

استادیار

• Genomics
• Animal Genetics
• Reproductive Biology
• +۳ مورد دیگر

Assist. Prof Emma Finlay is affiliated with the School of Biotechnology at Dublin City University . Her research focuses on genomics, animal genetics, and evolutionary biology, particularly in bovine and livestock populations. Her work spans genome-wide association studies, mitochondrial DNA diversity analysis, and functional characterization of genes involved in fertility and disease resistance. Key areas include: β-defensin genes in reproductive biology Population genetics of domestic animals Disease susceptibility in dairy cattle Emma Finlay has authored publications on topics such as bovine tuberculosis, mastitis resistance, and ancient DNA studies, contributing to understanding genetic diversity and evolutionary history.

Martin Craneمشاهده پروفایل

استاد

• Computational Finance
• Complex Systems
• Time Series Analysis
• +۱ مورد دیگر

Martin Crane is Professor and Head of School at Dublin City University School of Computing. Funded Investigator in ADAPT Centre, with PhD in Mechanical Engineering from Trinity College Dublin. Research spans computational finance, complex systems modeling, and high-performance computing applications. Key research areas: Time series analysis in finance/biology Complex systems in finance, immunology, and lifelogging Wavelet methods for market analysis Parallel computing for large-scale simulations Current projects examine cryptocurrency dynamics, healthcare analytics, and brain tumor segmentation using deep learning. Leads FinTech Fusion initiative exploring financial technology applications. Authored significant works on random matrix theory filters for portfolio optimization and agent-based HIV modeling.

Marija Bezbradicaمشاهده پروفایل

دانشیار

• Educational Analytics
• Computational Finance
• Complex Systems
• +۲ مورد دیگر

Dr. Marija Bezbradica serves as Associate Professor and COMBUS Programme Board Chair at Dublin City University's School of Computing. Her research bridges computational finance, educational analytics, and complex systems modeling. Key research areas include financial risk modeling using Bayesian methods, educational data mining for programming courses, and healthcare analytics for infection control. She holds affiliations with ADAPT (FinTech research), ARC-SYM (complex systems modeling), and Lero (software engineering). Recent publications demonstrate cross-disciplinary applications, spanning cryptocurrency market analysis, hospital readmission prediction, and synthetic data generation for medical conditions. Work frequently employs machine learning, graph-based methods, and advanced statistical modeling. No information is available regarding awards, supervised students, or specific laboratory facilities.

Gregory Provanمشاهده پروفایل

استاد

• Complex Systems
• Artificial Intelligence
• Diagnostics
• +۳ مورد دیگر

Professor Gregory Provan is a Full Professor and Programme Coordinator for BSc Data Science and Analytics at University College Cork's School of Computer Science and Information Technology. He directs the Complex Systems Laboratory and holds a PhD from the University of Oxford, with prior academic appointments at the University of Pennsylvania. His educational journey includes: BSE from Princeton University MSc from Stanford University DPhil from University of Oxford This foundation supports his interdisciplinary research approach. Professor Provan's research spans: complex systems design and analysis with applications in: Embedded diagnostics algorithms for large-scale systems Stochastic model-based diagnosis frameworks Automated benchmark model generation Sustainable energy system optimization Co-design of embedded systems His work bridges artificial intelligence, data analytics, and network architectures to solve real-world engineering challenges. Analysis of his extensive publication record reveals core themes: Advancements in model-based diagnosis and control Computational methods for complex systems Applications in sustainable energy and building automation Innovations in stochastic optimization and machine learning His recent work increasingly focuses on cybersecurity for cyber-physical systems and explainable AI. Professor Provan has secured significant research funding including: Science Foundation Ireland grants totaling over €1.2M Industry partnerships with Tyndall National Institute Enterprise Ireland support for competence centers His research group addresses fundamental challenges in complex systems engineering. He has supervised numerous doctoral candidates to completion, including: Jun Wang (Modeling real-world complex systems) Alie El-Din Mady (Networked control systems) Margarita Razgon (Constraint satisfaction problems) Ma Ji (Uncertainty visualization) Current doctoral researchers continue work on wireless sensor networks and analog system diagnosis. Honors include the 2008 Best Paper Award from the IEEE Prognostics and Health Management Conference for his work on approximation techniques in model-based diagnostics. Professor Provan leads the Complex Systems Laboratory which focuses on: Modeling and analysis of sustainable energy systems Diagnostics and control of large-scale networks Embedded system co-design The lab maintains collaborations with international research institutions and industry partners.