جست‌وجوی استاد و پژوهشگر

Kevin Meehanمشاهده پروفایل

مدرس

• Computer Vision
• Machine Learning
• Location Tracking
• +۳ مورد دیگر

Kevin Meehan is Lecturer in Computing at ATU, Principal Investigator at Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE), and Principal Investigator at Wireless Sensor Applied Research (WiSAR). His research explores computer vision, machine learning, and intelligent systems. Research focuses on: Deep learning approaches for computer vision Graph neural networks for biological applications Context-aware computing systems Pedestrian trajectory prediction Immune response classification His recent publications develop novel machine learning architectures for motion prediction and biological network analysis. He has secured over €400,000 in research funding and collaborated with 45+ SMEs on technology projects.

• Machine Learning
• Interactive Machine Learning
• Healthcare Applications
• +۵ مورد دیگر

Dr. Brian Mac Namee is an Associate Professor at the School of Computer Science, University College Dublin (UCD), and UCD Site Director at the Insight SFI Research Centre for Data Analytics since 2024. His research focuses on interactive machine learning, emphasizing human-centered model training, with applications in healthcare, agriculture, space technology, and virtual reality. He co-authored the textbook Fundamentals of Machine Learning for Predictive Data Analytics , translated into five languages. Education includes a PhD (2004) and BA (Mod) from Trinity College Dublin. He previously co-founded the Applied Intelligence Research Centre at Technological University Dublin and was a founding co-PI at CeADAR. He chairs the Artificial Intelligence Association of Ireland and directs training at Krisolis Ltd. Notable awards include the 2016 Data Science Award for Best Academic Research Team and UCD's Fiosraigh Research Excellence Award (2013). His teaching spans advanced machine learning, data science projects, and programming courses. He leads grants such as the SFI-funded Machine Learning & Virtual Reality for Pilot Training and co-directs the SFI Centre for Research Training in Machine Learning.

• Data Governance
• AI Ethics
• Data Protection
• +۴ مورد دیگر

Dr. Rob Brennan is an Assistant Professor in the School of Computer Science at University College Dublin. With 25 years of academic and industry experience, he specializes in data governance, AI ethics, and cybersecurity. His research integrates socio-technical systems analysis, data protection frameworks, and healthcare risk management. He leads the Value and Risk research challenge within the ADAPT Centre's Transparent Digital Governance initiative and coordinates projects like the ARK platform for risk governance. Education: BSc in Physics, Dublin City University MSc, Queen's University Belfast PhD in Governance, Dublin City University Professional Diploma in University Teaching and Learning, University College Dublin Research Interests: Data Governance & AI Accountability GDPR Compliance & Privacy Engineering Healthcare Risk Management Knowledge Graphs & Linked Data Cybersecurity & Incident Response Key Contributions: Co-PI of Science Foundation Ireland's Empower Data Governance project Coordinator of the €4M H2020 ALIGNED project on software/data engineering Developed the ARK platform for risk governance in healthcare and cybersecurity Grants & Awards: Best Paper Award at Extended Semantic Web Conference 2023 Principal Investigator for grants including the ARK-Virus platform (SFI-funded) Teaching & Mentorship: Coordinates courses on Cyber Risk Assessment, Incident Response, and Data Protection Supervises PhD students focusing on data governance and AI ethics Co-developed the MA in Data Protection and Privacy Law with Computing Professional Activities: Member of FAccT 2023 Program Committee Co-chair of the Irish Conference on Artificial Intelligence and Cognitive Science Contributor to international standards (OMG, IETF, 3GPP)

Andrew McCarrenمشاهده پروفایل

دانشیار

• Data Analytics
• Fintech
• Agriculture (Agtech)
• +۴ مورد دیگر

Dr. Andrew McCarren is an Associate Professor and Head of the School of Computing at Dublin City University (DCU). He holds a PhD and BSc from DCU and is a funded investigator in the Insight Centre for Data Analytics. His research focuses on applying data analytics to Fintech, Agriculture, Health, and Sports Performance. As a former industry professional with 20+ years experience in Agri, Engineering, and Pharmaceuticals, he bridges academic and industrial collaboration. Professional Affiliations: Fellow of Royal Statistical Society and Advance HE Key Roles: PI on SFI/EI projects, Visiting Professor at Princess Nourah bint Abdulrahman University Research spans software engineering (microservices architecture), health informatics (exercise interventions), and agri-tech (automated food processing). Over 100 publications across data science, sports analytics, and engineering.

• Machine Learning
• Statistics
• Model-Based Clustering
• +۵ مورد دیگر

Brendan Murphy is a Full Professor in the School of Mathematical Sciences at University College Dublin since 2015, previously holding a Professor role at the same institution (2007-2015) and a Lecturer position at Trinity College Dublin (1999-2007). He is a Principal Investigator at the Insight Centre for Data Analytics and actively works in Machine Learning & Statistics. Research Focus: His work centers on Model-based clustering Mixture models Applications in sports analytics, food science, microbiome studies, and public health Bayesian statistical methods High-dimensional data analysis Article Trends: Murphy's recent publications (2024-2025) emphasize soft clustering techniques, Bayesian mixture models, and their applications across diverse domains including metabolomics, political science, and oceanography. His work addresses challenges in variable selection, robust classification, and multi-omics integration.

Kathleen Curranمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۳ مورد دیگر

Prof. Kathleen Curran is a Professor at University College Dublin (UCD) and director of the UCD machine learning in medical imaging and diagnostics innovative research lab ( https://www.ucd-ml-mi.com/ ). She serves as an Affiliated Principal Investigator in the Centre for Biomedical Engineering, an INSIGHT funded investigator, and a funded investigator in the Science Foundation Ireland centre for research training in machine learning (ML-Labs). Her research integrates artificial intelligence, computer vision, and clinical medicine to develop interpretable AI solutions for medical diagnostics. Key focus areas include fetal ultrasound imaging, cardiac MRI reconstruction, neuroimaging for Alzheimer's disease and multiple sclerosis, and biomarker discovery for conditions like lymphangioleiomyomatosis and placenta accreta spectrum. She pioneers techniques in diffusion models, explainable AI, and multi-modal learning to address challenges in low-data medical scenarios. Analysis of her recent publications reveals dominant trends in applying generative models for medical data augmentation, developing uncertainty-aware diagnostic systems, and creating interpretable clinical AI tools. Her work consistently targets high-impact clinical applications including fetal development monitoring, cardiovascular disease management, and neurological disorder detection, with strong emphasis on real-world clinical implementation. Scientific recognition includes: 2019 InterTrade Ireland FUSION Project Exemplar Award (with Axial Medical Printing Ltd.) Three Enterprise Ireland Commercialisation Fund awards as Principal Investigator Horizon Europe consortium funding for SMASH-HCM project (Stratification, Management, and Guidance of Hypertrophic Cardiomyopathy Patients using Hybrid Digital Twin Solutions) Prof. Curran leads significant research funding initiatives including Horizon Europe and multiple Enterprise Ireland awards. Her group actively collaborates with industry partners like Axial Medical Printing Ltd. and participates in national research centers such as INSIGHT and ML-Labs, driving translational AI research from bench to bedside. The UCD machine learning in medical imaging and diagnostics lab ( https://www.ucd-ml-mi.com/ ) serves as her primary research hub, fostering interdisciplinary collaborations between computer scientists, clinicians, and biomedical engineers to advance clinical AI solutions.

Patrick Dennyمشاهده پروفایل

دانشیار

• Computer Vision
• Automotive Systems
• Medical Imaging
• +۳ مورد دیگر

Patrick Denny is an Associate Professor at the University of Limerick, affiliated with the Department of Computer Science & Information Systems, the Centre for Sustainable Digital (Re)Manufacturing, and Lero – the Research Ireland Centre for Software. His research focuses on computer vision, automotive systems, and medical imaging, with notable contributions to object detection, instance segmentation, and image processing in autonomous vehicles and healthcare. He holds patents in automotive camera systems and has authored over 38 research papers. His work addresses challenges such as rain impact on automated vehicle perception, medical image classification using graph neural networks, and optimizing camera exposure for automotive applications. He collaborates extensively on projects involving V2X communications and intelligent transportation systems. Denny’s research also extends to waste management through computer vision and medical imaging innovations. Patents: Over 10 patents in automotive imaging, including systems for calibrating image-capturing devices and thermal infrared sensors. Key Research Themes: Automotive perception, computer vision algorithms, medical image analysis, and sensor optimization. He actively engages in interdisciplinary projects, combining machine learning with real-world applications in transportation and healthcare.

• Animal Welfare
• Veterinary Ethics
• Farmed Animal Welfare
• +۵ مورد دیگر

Siobhan Mullan is a Professor at the School of Veterinary Medicine, University College Dublin. A veterinary surgeon who transitioned from clinical practice to research and teaching, she focuses on delivering large-scale, long-term improvements in animal welfare. She serves on the Farmed Animal Welfare Advisory Committee (FAWAC) and the Advisory Council on Companion Animal Welfare (ACCAW), influencing national policy. Her educational background includes a PhD from the University of Bristol. As a foundation diplomate of the European College of Animal Welfare and Behavioural Medicine (AWSEL sub-speciality), she ranks among only 120 EU-recognized veterinary specialists in this field. Mullan's research centers on developing valid methodologies to assess animal welfare that drive large-scale improvements across multiple species. Her work spans: Farmed animal welfare assessment methodologies Companion animal ethics and welfare Racehorse welfare in training and post-racing careers Veterinary ethics through her 'Everyday Ethics' column and co-authorship of 'Veterinary Ethics- Navigating Tough Cases' Her recent publications reveal a focus on practical welfare assessment tools across diverse species, from cattle and pigs to racehorses and companion animals. She has pioneered innovative approaches including machine vision monitoring for dairy welfare and ethical frameworks for animal welfare labeling, often bridging traditional welfare science with cutting-edge technology. Her scientific recognition includes being a foundation diplomate of the European College of Animal Welfare and Behavioural Medicine. Her policy influence extends through FAWAC and ACCAW memberships, where she helps shape animal welfare standards. Mullan supervises PhD students and has led significant projects including the AssureWel project and the Christian Ethics of Farmed Animal Welfare funded by the Arts and Humanities Research Council. Her collaborative approach spans multiple disciplines, working with industrial partners to integrate welfare outcome assessments into farm assurance schemes, delivering documented benefits for over 2 million farm animals annually. Her research team develops welfare assessment protocols emphasizing both scientific validity and practical implementation. She champions multi-disciplinary collaborations that combine animal welfare science with ethics, policy development, and technological innovation to create meaningful improvements in animal lives.

• Affective Computing
• Machine Learning
• Computer Vision
• +۳ مورد دیگر

Jonny O'Dwyer is a Lecturer in the Department of Accounting and Business Computing at the Faculty of Business and Hospitality. His research focuses on affective computing, leveraging eye tracking, speech, and head cues for continuous emotion prediction. He employs machine learning and computer vision techniques to advance human-computer interaction and emotion recognition systems. O'Dwyer has published four peer-reviewed conference papers, with two in 2017 and two in 2019, exploring multimodal data fusion and real-time affect prediction models. His work emphasizes interdisciplinary approaches, combining artificial intelligence with bioinformatics to address challenges in emotion analysis. Recent studies highlight applications in facial expression analysis, convolutional neural networks, and discrete-time feature extraction. O'Dwyer’s contributions aim to enhance communication environments and human-computer interfaces through multimodal sensing and open-source software integration.

• Robotics
• Unmanned Aerial Vehicles
• Computer Vision
• +۳ مورد دیگر

Ben Bartlett is a Researcher at the University of Limerick's School of Engineering, specializing in robotics and unmanned systems for environmental and infrastructure applications. His work bridges engineering innovation with practical solutions for challenging real-world environments. His research focuses on: Development of UAV systems for wildlife monitoring and offshore wind farm surveys Cooperative multi-robot path planning for bridge and infrastructure inspection Fault-tolerant control systems for inaccessible environments Maritime robotics using integrated aerial and surface vehicles Automated 3D reconstruction of unknown structures using LiDAR Analysis of his 2023-2025 publications reveals a consistent trend toward real-time, automated systems that balance wide-area coverage with high-resolution precision. His work demonstrates particular strength in adapting robotic systems to dynamic environments like offshore wind farms, aging infrastructure, and maritime settings, with emphasis on efficiency, safety, and cost-effectiveness through modular design and fault tolerance. Contact: Ben.Bartlett@ul.ie

Martin J. Hayesمشاهده پروفایل

استاد

• Artificial Intelligence
• Computer Vision
• Wireless Communications
• +۵ مورد دیگر

Professor Martin J. Hayes serves in the Department of Electronic and Computer Engineering at the University of Limerick's Faculty of Science and Engineering. His institutional affiliation includes campus location ERB2-021 and contact details: email Martin.J.Hayes@ul.ie and phone +353 (0)61 202577. His research concentrates on Artificial Intelligence and Computer Vision applications within Smart Manufacturing and Autonomous Vehicles . Key specialties include deep learning for defect detection, visual question answering systems, and real-time failure monitoring in industrial environments. He also investigates interoperable IoT security frameworks and private 5G network implementations for Industry 4.0. Analysis of recent publications (2023-2025) reveals dominant themes in AI-driven manufacturing solutions and autonomous driving technologies. His work consistently addresses data-constrained training environments and real-time performance requirements, with growing emphasis on human-machine interaction patterns and subjective evaluation frameworks for vision systems. Scientific Awards: No scientific awards were documented in available sources Advising and Grants: While specific student advisement records and grant details were not provided, Professor Hayes' extensive publication output across manufacturing automation, autonomous systems, and wireless communications indicates active leadership in multiple research initiatives. His involvement in the REEdI (Rethinking Engineering Education in Ireland) project demonstrates commitment to educational innovation alongside technical research.

• Signal Processing
• Machine Learning
• Computer Engineering
• +۳ مورد دیگر

Ehsan Namjoo serves as a Research Fellow in the Department of Electronics & Computer Engineering at the University of Limerick, with a primary affiliation at Lero – the Irish Software Research Centre. His multidisciplinary work bridges theoretical signal processing, machine learning applications, and hardware implementation for real-world systems. His research spans signal processing (DOA estimation under non-ideal noise conditions, EEG source imaging), machine learning (explainable AI for medical diagnostics, feature selection in cancer detection), and computer engineering (polar code decoders, visible light communication systems). Notable biomedical applications include breast cancer diagnosis and epileptic source analysis, while cybersecurity work focuses on intrusion detection in cloud environments. Recent publications (2021-2025) reveal a consistent trajectory toward developing lightweight, interpretable models for tabular medical data alongside robust signal processing frameworks for communication systems. His work increasingly integrates hardware-aware algorithms, particularly in polar coding implementations, and emphasizes practical validation through experimental demonstrations in visible light networks. As an active Lero researcher, Namjoo participates in Ireland's national software research ecosystem, contributing to interdisciplinary projects that connect theoretical innovations with healthcare, communications, and security applications through collaborative frameworks.

John Breslinمشاهده پروفایل

استاد

• Data Science
• Artificial Intelligence
• Social Semantics
• +۷ مورد دیگر

John Breslin is a Personal Professor in Electronic Engineering at the University of Galway, leading the TechInnovate/AgInnovate programs. His roles include Director of the Insight (Data Analytics) and VistaMilk (AgTech) research centers. He has authored 350+ publications and co-created the SIOC framework, widely used in web applications. His research spans Data Science, AI, Semantic Web, IoT, and Entrepreneurship. He has won multiple awards, including the Best Irish-Published Book and IIA Net Visionary Awards. His teaching spans 25 years, covering topics like Digital Control Systems and Innovation. He co-founded boards.ie, StreamGlider, and leads initiatives in Galway's innovation ecosystem. Research Interests: Data Science, AI, Social Semantics, IoT, Agricultural Technology, and Innovation. He is ranked top in Engineering and Computer Science citations at the University of Galway. His work contributes to UN SDGs related to Industry, Innovation, and Infrastructure. Education: Details not explicitly provided in text. Collaborations include Bosch, Cisco, IBM, and Harvard Medical School. Active in industry partnerships and startups, including the PorterShed Innovation District. Awards: Best Paper Awards, Entrepreneurship Recognition, and Academic Excellence. Supervised nearly 30,000 ECTS across modules, with a focus on graduate and postgraduate tech innovation programs.

• Machine Learning
• Computer Vision
• Human Motion Analysis
• +۳ مورد دیگر

Dr. Timilehin Aderinola is a Marie Curie Postdoctoral Fellow at the School of Computer Science, University College Dublin. His research focuses on applying machine learning and computer vision to analyze human movement, particularly in neurological conditions like Parkinson's disease. He holds a PhD in Information Technology from Multimedia University, Malaysia (2022), and master's and bachelor's degrees from Federal University of Technology Akure, Nigeria (2017 and 2012). Education: B.Eng. (Hons) in Electrical and Electronic Engineering, Federal University of Technology Akure (2012) M.Sc. in Computer Science, Federal University of Technology Akure (2017) PhD in Information Technology, Multimedia University Malaysia (2022) Research Interests: Machine Learning and Computer Vision Human Motion Analysis (e.g., gait analysis, fall detection) Applications in healthcare and surveillance Awards: Silver Medal (2021) for commercialization potential of PhD work Honourable Mention (2021) at NP2C poster competition Advising/Grants: Co-supervised research projects on exercise classification and human pose estimation. Engaged in peer review for conferences like ECML-PKDD and ICoICT. Labs/Teams: Active in the Insight Centre for Data Analytics at UCD, focusing on NeuroInsight Marie Skłodowska-Curie Fellowship projects analyzing mobility data for neurological patients.

Suzanne Littleمشاهده پروفایل

استاد

• Computer Vision
• Media Analytics
• Machine Learning
• +۲ مورد دیگر

Professor Suzanne Little is a Full Professor at Dublin City University's School of Computing and SFI Principal Investigator at the Insight Centre for Data Analytics. She holds a PhD from the University of Queensland and leads research in media analytics, computer vision, and machine learning. Her work develops methods for analyzing multimedia content including video analysis for surveillance, sports analytics, transportation, and medical imaging. Research focuses on: Content-based multimedia indexing and retrieval Computer vision for object/event detection in video Bias analysis in deep learning models Edge computing for video analytics Optimization of neural network architectures Her recent publications address bias mitigation in AI systems, efficient object detection methods, and novel applications of event cameras. Professor Little co-directs the SFI Centre for Research Training in Artificial Intelligence and contributes to the iForm Advanced Manufacturing Centre. She has led multiple EU projects in multimedia and big data, including the Smart Stadium IoT initiative with Croke Park. Her work has been featured in media outlets including RTE, Silicon Republic, and The Irish Times.