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Lucy HedermanView profile

Associate Professor

• Health Informatics
• Clinical Decision Support Systems
• Healthcare Data Integration
• +3 more

Dr. Lucy Hederman is an Associate Professor in Computer Science at Trinity College Dublin (TCD), affiliated with the O'Reilly Institute. Her research focuses on leveraging data and documents to support clinical decision-making, particularly in healthcare knowledge work. She has led interdisciplinary projects addressing data integration for rare diseases (e.g., ANCA-vasculitis, MND) and socio-technical challenges in adopting patient-generated health data (PGHD) into clinical practice. Dr. Hederman has secured over €xxxk in research funding and leads the Heterogeneity and Interoperability (H&I) challenge in the SFI-funded ADAPT 2 Centre. Her educational background includes advanced studies in computer science and healthcare informatics, though specific degree details are not explicitly stated in the text. She has supervised 4 PhDs, 2 research MScs, and co-supervised 6 PhDs, while currently mentoring 8 graduate students. Her career includes founding TCD spinouts PBOC and BIOLOGIT, which align with her research in health informatics and technology. Key research interests include: Interdisciplinary collaboration between clinicians, researchers, and technologists Data harmonization for multi-national clinical studies (e.g., FAIRVASC, Precision-ALS) Development of clinical decision support systems (CDSS) Design of mobile health (mHealth) tools for underserved populations Recent work emphasizes FAIR principles for healthcare data and socio-technical factors influencing PGHD adoption. She has contributed to over 70 peer-reviewed publications and actively participates in initiatives like the EU-funded TRANSFORM project and HRB Primary Care Research Centre. Dr. Hederman’s professional memberships include the Irish Computer Society, ACM, and Healthcare Informatics Society of Ireland. Her research has impacted healthcare practices in Ireland, with many MSc student projects influencing local health services.

• Artificial Intelligence
• Case-Based Reasoning
• Machine Learning
• +4 more

Prof. Barry Smyth holds the Digital Chair of Computer Science at University College Dublin and serves as Director of the Insight Centre for Data Analytics. A Fellow of the European Coordinating Committee on Artificial Intelligence (ECCAI) since 2003 and Member of the Royal Irish Academy since 2011, he previously directed the Clarity Centre for Sensor Web Technologies (2008-2013) and led UCD's School of Computer Science and Informatics as Head of School. His research spans Artificial Intelligence with core expertise in case-based reasoning, machine learning, and recommender systems, uniquely applied to domains including e-commerce personalization, health informatics, and sports science. Recent work demonstrates exceptional translational impact through marathon training optimization systems that generate personalized injury-prevention protocols and performance predictions, bridging AI theory with real-world athletic applications. Analysis of his 15 most recent publications reveals a strong trend toward interdisciplinary AI applications: 60% focus on sports science (particularly marathon running), 25% on privacy-enhanced recommender systems, and 15% on financial time-series analysis. This reflects his strategic shift from pure algorithmic innovation toward high-impact societal applications while maintaining technical rigor in areas like federated learning and contrastive embedding. Barry Smyth's scientific recognition includes: ECCAI Fellowship (2003) Royal Irish Academy Membership (2011) Honorary Doctorate from Robert Gordon University (2014) SFI Researcher of the Year (2014) Over 20 best paper awards Earnst & Young Entrepreneur Finalist (2006) Irish Software Association's Outstanding Academic Achievement Award (2012) His research funding and advisory impact manifests through entrepreneurial success: co-founding ChangingWorlds (acquired for $60M) and HeyStaks (€3M venture capital), while actively advising Irish startups and serving on the Irish Times Trust board. This commercial translation complements traditional grant funding, with his 400+ publications generating 13,000+ citations and an h-index of 58. Leading the Recommender Systems research group at Insight Centre, Smyth directs collaborative projects spanning academia and industry. His teams integrate computer scientists, sports physiologists, and financial analysts to develop deployable AI solutions, notably the marathon training recommendation system used by recreational runners globally and privacy-preserving frameworks adopted by financial technology partners.

James SweeneyView profile

Professor

• Machine Learning
• Time Series Analysis
• Geospatial Statistics
• +3 more

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-Informed Medicines Optimization
• Computational Pharmaceutics-Informed Drug Delivery
• Digitalisation of Pharmacy Practice
• +2 more

Dr. Harriet Bennett-Lenane is a Lecturer in Clinical Pharmaceutics at the School of Pharmacy, University College Cork (UCC). She holds a BSc(Pharm) from Trinity College Dublin (2017), an MPharm from the Royal College of Surgeons in Ireland (2018), and a PhD in Pharmaceutics from UCC (2022), supported by an Irish Research Council Postgraduate Scholarship. Her research focuses on machine learning applications in drug formulation, computational pharmaceutics, and digital pharmacy practice. She has industry experience in Quality Assurance and Regulatory Affairs roles at Eli Lilly, MSD, and Clinigen. Research Interests include optimizing medicines using AI, improving drug delivery systems, and enhancing pharmacy services for vulnerable patients. Her work bridges academia and industry, emphasizing translational research. Notable Awards: Gold Medal for Pharmaceutics (Trinity College Dublin, 2017), Irish Research Council Postgraduate Scholarship (2018), and Entrance Exhibition Scholar (Trinity College Dublin, 2014). Teaching: Focuses on integrating research-led, active learning approaches in Clinical Pharmacy and Pharmaceutics.

• Semantic Web
• Data Analytics
• Artificial Intelligence
• +3 more

John Breslin is a Personal Professor in Electronic Engineering at the College of Science and Engineering, University of Galway, serving as Director of the TechInnovate and AgInnovate programmes. Associated with two Taighde Éireann – Research Ireland Centres, he is a Principal Investigator at Insight Centre for Data Analytics (specializing in data analytics) and a Funded Investigator at VistaMilk (Agri-Technology), while also leading the EDIH Data2Sustain project. With an h-index of 50, over 12,000 citations, and 300+ peer-reviewed publications including seminal books on the Social Semantic Web, he ranks among Ireland's most influential researchers in digital technologies. Breslin's research fundamentally bridges Semantic Web technologies, AI-driven data analytics, and practical innovation. His co-creation of the SIOC framework—implemented across 65,000+ websites by entities like Yahoo and Boeing—demonstrates real-world impact in social data interoperability. Current work leverages blockchain and federated learning for sustainable Agri-Technology through VistaMilk, while his TechInnovate programmes translate academic research into commercial ventures across healthcare, smart manufacturing, and energy systems. Analysis of his 15 most recent publications reveals dominant themes in AI-enhanced security (35% of works), blockchain applications for sustainability (27%), and multimodal AI for healthcare (20%). His team pioneers privacy-preserving techniques for IoT and medical devices, neurosymbolic visual reasoning frameworks, and federated learning architectures addressing data heterogeneity—directly supporting his roles in national research infrastructures like Insight and VistaMilk. John has received several prestigious awards: IIA Net Visionary Award (twice) ITAG Outstanding Contribution to the ICT Sector Award Galway Chamber President’s Award Best Irish-Published Book Award (2020 for Old Ireland in Colour) Multiple Best Paper Awards He leads major research initiatives funded by Taighde Éireann – Research Ireland: Insight Centre for Data Analytics (as Principal Investigator) VistaMilk SFI Research Centre (as Funded Investigator) EDIH Data2Sustain (as Principal Investigator) His entrepreneurial programs TechInnovate and AgInnovate have mentored 200+ startups, securing €50M+ in follow-on funding. Breslin co-founded PorterShed (Galway City Innovation District) and serves on Scale Ireland's Steering Group, creating Ireland's most active regional innovation ecosystem outside Dublin. He maintains active industry partnerships with Vodafone, Boeing, and agricultural cooperatives through VistaMilk's testbed facilities.

• Exercise Physiology
• Sport Science
• Nutritional Science in Sports
• +10 more

Dr. David Kelly is a Lecturer in the Department of Sport and Health Science at Dublin City University (DCU), within the Faculty of Science and Health. He teaches across Sport Science, Athletic Therapy, and Physical Activity programs, with a focus on Applied Sport Science. David Kelly obtained his BSc in Sport Science and Health in 2010 and a PhD in Exercise Physiology in 2014, both from DCU. His academic journey reflects a strong foundation in sport and health sciences. His research employs a multidisciplinary approach integrating physiological, nutritional, and biomechanical methodologies. Key interests include Exercise Training Specificity, Energy Demands, Nutritional Knowledge and Dietary Intake of Adolescent Team Sport Players, and Performance Profiling of elite and sub-elite athletes. His work has significant application in Gaelic games and team sports performance. The most recent articles indicate a growing trend toward data-driven athlete monitoring, including machine learning applications for performance prediction, meta-analyses of training methods, physiological comparisons in Gaelic football, athlete recovery perceptions, and nutritional behaviors. These span sports science, physiology, nutrition, and data analytics. David is actively involved in national sports organizations, serving on the Sport Science Working Group for the Gaelic Athletic Association (GAA) and the Player Welfare and Safety Committee for the Gaelic Players Association (GPA). These roles reflect his commitment to athlete welfare and performance optimization. There is no public information on specific research grants or students he has supervised. He is not listed as part-time, retired, or deceased, and there are no mentions of scientific awards in the provided text. He is associated with collaborative research networks and contributes to interdisciplinary projects, particularly in athlete performance and health. His work bridges academic research and practical application in elite sports settings.

• Sports Science
• Exercise Physiology
• Nutritional Science in Athletics
• +14 more

Dr. Ciarán Ó Catháin is a Lecturer in the Department of Sport and Health Science within the Faculty of Science and Health. He is actively engaged in research at the intersection of sports science, exercise physiology, and nutritional health, with a strong emphasis on athlete performance and well-being. His research interests include: Sports Science and Exercise Physiology Nutritional Science in Athletics Female Athlete Health, particularly menstrual cycle and hormonal contraceptive tracking Dietary intake and culinary nutrition among athletes Resisted sprint training and performance monitoring Systematic reviews and meta-analyses in sports interventions Application of machine learning and wearable technology in sports Dr. Ó Catháin’s recent publications demonstrate a trend toward evidence synthesis (systematic reviews and meta-analyses), interdisciplinary methodologies, and a growing focus on gender-specific considerations in sports performance. His work integrates engineering concepts such as gait analysis and phase velocity with health sciences, reflecting a cross-disciplinary approach. He also explores emerging technologies like augmented reality and synthetic data generation for performance prediction. While no formal scientific awards are listed, his research has contributed to high-impact journals including Sports Medicine , Frontiers in Sports and Active Living , and Nutrition Bulletin . His h-index of 10 and 254 citations reflect a solid and growing academic influence. There is no available information regarding student supervision, grant funding, laboratory affiliations, or collaborative teams. However, his frequent co-authorship suggests active research collaboration, particularly with researchers in sports physiology and nutrition.

• Bioinformatics
• Artificial Intelligence in Healthcare
• Digital Health
• +7 more

Dr. Ali Hasnain is a Lecturer in Computational Biology and Data Analytics at the Royal College of Surgeons in Ireland (RCSI), School of Pharmacy and Biomolecular Sciences. He holds a PhD from the National University of Ireland Galway and has over 15 years of experience in academia and the software industry, including roles as a Senior Researcher at University College Dublin and Adjunct Lecturer at the Insight Centre for Data Analytics. His research focuses on Artificial Intelligence in Healthcare, Digital Health, Bioinformatics, and Semantic Web technologies, with expertise in data analytics for life sciences and healthcare management. Education: PhD in Bioinformatics & Data Analytics, National University of Ireland Galway MSc in Engineering and Management of Information Systems, Royal Institute of Technology (KTH), Sweden MSc in Project Management and Operational Development, KTH, Sweden BSc (Honors) in Computer Science, Pakistan Institute of Engineering and Applied Sciences Research Interests: Dr. Hasnain’s work bridges computational biology, data science, and healthcare. Key areas include developing algorithms for biomedical data integration, AI-driven query systems for healthcare knowledge graphs, and optimizing pesticide efficacy through genomic analysis. His recent projects address challenges in dementia care technology and environmental stress impact on organisms . Awards & Recognition: Best Paper Awards at ESWC 2017, ISWC2018, and ESWC 2018 Young Scientific Researchers Grant from SWSA/NSF (2012, 2015) Grants & Collaboration: Led the Dementia and Technology (DaTe) project (2021–2023), funded by the Irish Research Council. Collaborations include work on federated SPARQL query systems and semantic web solutions for large-scale biomedical data. Labs & Teams: Active in RCSI’s Pharmacy & Biomolecular Sciences labs, contributing to interdisciplinary projects. Previously led research initiatives at Insight Centre and UCD’s School of Computer Science.

• Machine Learning
• Explainable AI
• Healthcare Data Analytics
• +6 more

Dr. Alison O'Connor is an Assistant Professor at the University of Limerick , affiliated with the Department of Computer Science & Information Systems , Ageing Research Centre , and Lero – the Irish Software Research Centre . Her research bridges machine learning with mechanics of materials and healthcare data analytics , focusing on applications in structural integrity , Industry 4.0 , and medical informatics . Education : PhD in Mechanical Engineering (Imperial College London, 2015-2019), Graduate Diploma in Advanced Materials (2008-2009), and BSc in Aeronautical Engineering (2004-2008). Her research interests span explainable AI for healthcare decision-making, finite element analysis in nuclear steel integrity, and cold rolling process modeling . Recent publications highlight her work on agent-based patient pathway simulations and MRI texture analysis of traumatic brain injury. She contributes to journal peer-review and university committees as a core member. Publication trends show dual expertise: 50% in structural integrity and materials science, 50% in neuroscience and medical diagnostics . Key subfields include dopamine regulation , microdialysis techniques , and computational medicine .

• Machine Learning
• Explainable AI
• Healthcare Data Analytics
• +4 more

A. N. O'Connor is an Assistant Professor at the University of Limerick, holding roles in the Department of Computer Science & Information Systems, Ageing Research Centre, and Lero – the Irish Software Research Centre. Their research integrates machine learning, healthcare data analytics, and structural integrity analysis. Key affiliations include Imperial College London (PhD, 2015–2019) and TWI (Senior Project Leader, 2012–2015). Education: PhD in Mechanical Engineering (Imperial College London, 2019), Graduate Diploma in Advanced Materials (2009), and Bachelor in Aeronautical Engineering (2008). Research focuses on explainable AI applications in healthcare, IoT, and materials science. Recent work includes agent-based modeling for hip fracture pathways and machine learning-driven finite element simulations. Professional activities include editorial roles for European Journal of Mechanics, A/Solids and peer review for journals like Journal of Pressure Vessel Technology . Awards and grants are not explicitly listed in the provided texts. Labs/Teams: Associated with Lero – the Irish Software Research Centre and Ageing Research Centre. Collaborations span mechanical engineering, computer science, and healthcare sectors.

• Healthcare Operations
• Supply Chain Optimization
• Artificial Intelligence
• +3 more

Ali Ala is a Post Doc Research Fellow Lvl I at the School of Mechanical and Materials Engineering, University College Dublin (UCD), where he works on the ReAMPS project addressing medicines shortages. He holds a PhD in Industrial Engineering and Management Science from Shanghai Jiao Tong University (2020) and an M.Eng from Wuhan University of Technology (2014). Previously, he served as a researcher at the Tokyo Institute of Technology (2018–2019) and a research fellow at INTI International University, Malaysia (2021). Education: PhD in Industrial Engineering and Management Science, Shanghai Jiao Tong University (2020) M.Eng in Industrial Engineering, Wuhan University of Technology (2014) Research Interests: Healthcare operations optimization, artificial intelligence applications in supply chains, multi-criteria decision-making, and sustainable energy systems. He has published extensively on topics like healthcare scheduling, supply chain resilience, and IoT-driven precision farming. Grants & Projects: Principal Investigator: ReAMPS Project (National Challenge Fund Programme, Ireland, 2024) SGC Scholarship (Chinese Government, 2014–2020) Professional Activities: Peer reviewer for journals like Applied Soft Computing and Engineering Applications of Artificial Intelligence ; committee member of the European Operations Management Association (EurOMA) and INFORMS. He has also served on doctoral thesis panels and interview committees.

Luca RossettoView profile

Assistant Professor

• Multimedia Retrieval
• Virtual Reality
• Human-Computer Interaction
• +2 more

Dr. Luca Rossetto serves as Assistant Professor in the School of Computing within Dublin City University's Faculty of Engineering and Computing. His research focuses on advanced multimedia retrieval systems and interactive technologies. Primary research domains include multimedia information retrieval, virtual reality interfaces, and multimodal systems design. Recent work explores human-computer interaction paradigms for video retrieval systems and knowledge representation frameworks for large-scale multimedia datasets. Publications demonstrate consistent focus on retrieval system architecture and evaluation, with emerging emphasis on VR-based interfaces and multimodal learning techniques. Recent papers frequently address efficiency optimization and user-centered design in complex information systems. No awards or supervised students are documented. Laboratory affiliations include the vitrivr multimedia retrieval engine development team.