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Prof. Liam Murphy is a Full Professor of Computer Science & Informatics at University College Dublin (UCD) and Director of the Performance Engineering Laboratory. He holds a B.E. from UCD, M.Sc. and Ph.D. from UC Berkeley. His research focuses on performance engineering of networks, software systems, and multimedia transmissions. He has published over 150 peer-reviewed papers and is an IEEE member and Fellow of the Irish Computer Society. Education: B.E. in Electrical Engineering, UCD (1985) M.Sc. & Ph.D. in Electrical Engineering & Computer Sciences, UC Berkeley (1988, 1992) Research Interests: Dynamic resource allocation in networks Cloud computing efficiency Software performance engineering Wireless multimedia systems Quality of Service (QoS) optimization Recent work emphasizes energy-efficient cloud workflows, multi-objective data center optimization, and decentralized traffic simulation. Grants & Awards: Fellow of the Irish Computer Society (2007) Conference Paper Awards (2004, 2002, 2001) Principal Investigator in multiple funded projects (e.g., EU-funded traffic simulation, cloud resource allocation) Advising & Labs: Directed 24 Ph.D. and 8 M.Sc. students. Leads the Performance Engineering Laboratory (PEL), focusing on distributed systems, cloud efficiency, and network performance. Collaborates on industry-relevant projects like crovan (UCD/DCU campus company). Teaching: Coordinates courses on computer science fundamentals, distributed systems performance, and software engineering at UCD.

• Computer Science
• Networking
• Telecommunications
• +4 more

Conor Ryan is a Professor in the Department of Computer Science & Information Systems at the University of Limerick. He is a Science Foundation Ireland-funded Investigator since 2002 and a member of multiple research centres including Lero – the Irish Software Research Centre and the Limerick Digital Cancer Research Centre. His research focuses on Genetic Programming, Grammatical Evolution, and their applications in domains like healthcare analytics, digital circuit design, and financial modeling. He has authored over 250 publications, with recent work emphasizing automated feature selection in medical diagnostics, neural architecture search, and blockchain ecosystems. Teaching includes courses on Foundations of Computer Science and Computer Games Programming. Research interests span evolutionary computation, machine learning, and interdisciplinary applications. Collaborations involve global institutions, reflecting his work's impact across computer science, engineering, and healthcare. His research has addressed challenges in breast cancer diagnosis via genetic algorithms, cryptocurrency volatility prediction using random forests, and automated generation of digital circuits. Ongoing projects explore interpretability in AI, energy-efficient computing, and sustainable transport systems through predictive analytics. Professional memberships include roles in the Centre for Research Training in Foundations of Data Science and the Data-Driven Computer Engineering Research Centre, underscoring his commitment to interdisciplinary innovation.

• Genetic Programming
• Genetic Algorithms
• Grammatical Evolution
• +7 more

Dr. Jon Gruda is an Assistant Professor and Lecturer in Organisational Behaviour at Maynooth University's School of Business. He holds a PhD in Management from emlyon Business School (France) and a joint Dr. rer. nat. in Psychology from Goethe University Frankfurt. His research focuses on relational leadership, dark leadership traits, anxiety in the workplace, and personality psychology, with a strong emphasis on integrating machine learning and AI methodologies. Gruda has been recognized with prestigious awards, including selection for the Lindau Nobel Laureates Meeting in Economic Sciences (2020). His interdisciplinary work includes predicting anxiety and personality traits via social media data analysis. He serves as an Associate Editor for journals like Personality and Individual Differences and Frontiers in Psychology . Education PhD in Management, emlyon Business School (2012–2017) Dr. rer. nat. in Psychology, Goethe University Frankfurt (2012–2017) MSc in Affective Neuroscience, Maastricht University (2018) MSc in Management Research, emlyon Business School (2012–2014) Triple MSc in Management, City University London/ESCP Europe (2010–2012) BSc in International Business & Management, University of Groningen (2007–2010) Research Interests Gruda’s work bridges leadership studies, personality psychology, and data science. Key areas include: Dark leadership traits (e.g., narcissism, Machiavellianism) and their organizational impacts Machine learning applications for detecting anxiety and personality traits via social media Cross-cultural studies on leadership perceptions and attachment orientations Impact of physiological/psychosocial factors on leadership effectiveness Publications & Projects Recent projects include predicting state-level health outcomes linked to narcissism and developing algorithms to track anxiety using Twitter data. Over 20 peer-reviewed articles since 2017 highlight his contributions to organizational behavior and computational social science. Awards 7th Lindau Nobel Laureates Meeting on Economic Sciences (2020) Benedictine University Award (Academy of Management, 2020) Wharton Global Faculty Development Program (2020) Grants & Collaborations Gruda leads projects on pro-environmental behavior and collaborates with the National Care Experience Programme on healthcare feedback analysis. Seed funding includes €301,930 for computational text analytics in healthcare. Labs & Teams Interdisciplinary research collaborations span psychology, data science, and public health, with a focus on applying machine learning to organizational challenges.

• Organizational Behavior
• Leadership Studies
• Personality Psychology
• +4 more

David Lillis is an Associate Professor in the School of Computer Science at University College Dublin (UCD). His research focuses on Natural Language Processing (NLP), Artificial Intelligence (AI), and their applications in legal and forensic contexts. He leads projects like CeADAR (Ireland’s Applied AI Center) and the Transpire project, collaborating with organizations such as Corlytics and the Department of Enterprise, Trade and Employment. He holds adjunct roles as a Guest Professor at Beijing University of Technology’s Data Mining and Security Lab and has been a Fulbright Scholar at the University of New Haven’s Cyber Forensics Research and Education Group. Education: B.A. (Hons) in Law and Accounting, University of Limerick Higher Diploma in Computer Science, UCD M.Sc., Ph.D. in Computer Science, UCD Professional Certificate in University Teaching & Learning, UCD Research Interests: Legal AI, digital forensics, machine learning, multi-agent systems, and information retrieval. Recent work includes NLP for regulatory analysis, crop yield prediction via neural networks, and AR-driven decision support systems. Grants & Projects: Principal Investigator: Transpire (AI Platform for Regulation) SFI Funded Investigator: CONSUS (Crop Optimization) PI: CeADAR Technology Centre Teaching roles include Deputy Programme Director for Software Engineering at Beijing-Dublin International College (BDIC) since 2014. Labs & Groups: UCD Forensics and Security Research Group, ML-Labs (SFI Centre for ML Training), and the Data Mining and Security Lab (BJUT).

• Natural Language Processing
• Artificial Intelligence
• Digital Forensics
• +4 more

Dr. Dongyun Nie is an Assistant Professor at Dublin City University's School of Computing. She holds a PhD in Computer Science with a specialization in Customer Relationship Management. Her core research explores customer lifetime value, forecasting, data mining, and record linkage. Her recent publications demonstrate interdisciplinary work spanning health informatics, sports analytics, and environmental data engineering. Research predominantly focuses on machine learning applications for real-world data challenges including eye-tracking systems, lifelog analytics, and public health data infrastructure. Teaching responsibilities include modules on Machine Learning (CA4109), Enterprise Systems Configuration (CA2049), and Web Design (CA106), integrating research expertise into computing education.

• Customer Lifetime Value
• Data Mining
• Forecasting
• +2 more

Prof. Zena Moore is a renowned academic and clinician serving as Professor and Head of the School of Nursing & Midwifery at RCSI, University of Medicine and Health Sciences. She holds adjunct professorships at Curtin University (Australia), Griffith University (Australia), Cardiff University (UK), Ghent University (Belgium), and Fakeeh College for Medical Sciences (Saudi Arabia). Her research focuses on wound healing, pressure ulcer prevention, and nursing education, with over 300 publications. She leads the Skin Wounds and Trauma (SWaT) Research Centre and chairs multiple international bodies including the European Pressure Ulcer Advisory Panel. Education: PhD in Wound Healing (RCSI), MSc in Leadership in Health Education (RCSI), MSc in Wound Healing (University of Wales), FFNMRCSI, and Diplomas in Management and Nursing. Research Interests: Wound pathophysiology, pressure ulcer risk assessment, technologies for early detection, and healthcare equity. Awards: 2022 Lifetime Achievement Award from World Union of Wound Healing Societies. Her work spans over 50 funded projects, including grants from Science Foundation Ireland and the National Health and Medical Research Council. She has supervised numerous research projects on topics like pressure ulcer prevention algorithms and eHealth interventions.

• Wound Healing & Tissue Repair
• Pressure Ulcer Prevention
• Nursing & Midwifery Education
• +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.

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

Aonghus Lawlor is an Assistant Professor/Lecturer in Computer Science at the School of Computer Science, University College Dublin. His roles include coordinating modules such as Software Engineering, Data Structures, Machine Learning, and Final Year Project Foundations. He holds an Orcid identifier: 0000-0002-6160-4639. His research focuses on machine learning applications in medical imaging (e.g., MRI, CT), sports science, and healthcare systems. Notable areas include AI-driven diagnostics, cybersecurity in radiology, and genomics for agricultural optimization. Recent work explores ChatGPT4-vision in MS progression, knee osteoarthritis grading via anomaly detection, and reinforcement learning in exercise prescriptions. Professional activities include committee roles in ACM Recommender Systems and Intelligent User Interfaces, grant assessments, and peer reviewing. He has published 137+ outputs, emphasizing interdisciplinary AI solutions with clinical and agricultural impact. Teaching responsibilities span foundational CS courses to advanced ML and project modules. No formal awards are listed, but his work demonstrates contributions to AI ethics, health informatics, and agricultural genomics.

• Machine Learning
• Medical Imaging
• Health Informatics
• +3 more

John Byabazaire is a Research Fellow at the School of Computer Science, University College Dublin (UCD). He holds a PhD in Computer Science from UCD (2024), following a BSc (Gulu University, 2013) and MSc (Waterford Institute of Technology, 2018). His research focuses on IoT systems for data collection, remote sensing, AI-driven end-to-end system management, and fog analytics. He has held academic roles including Assistant Lecturer at Gulu University (2018–2019) and teaching roles at UCD since 2019, including Occasional Lecturer and Senior Teaching Assistant. His research spans smart agriculture, data quality in IoT, and education technology. Notable contributions include frameworks for yield mapping in precision agriculture, trust-based data validation in IoT, and machine learning approaches for livestock health monitoring. He has secured grants like the National ICT Initiatives Support Program (Uganda Government, 2019–2020). Teaching includes courses on cloud computing, web development, and distributed systems. His articles emphasize IoT data quality, agricultural analytics, and educational technology innovation. He actively promotes technology adoption in African education and agriculture sectors through collaborative projects.

• IoT Systems
• Data Quality
• Fog Analytics
• +7 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.

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

Liadh Kelly is an Assistant Professor in the Department of Computer Science at Maynooth University's Faculty of Science & Engineering. She supervises PhD students in applied artificial intelligence, focusing on intelligent search, ubiquitous computing, and multimodal information access. She is affiliated with the ADAPT SFI Research Centre, SFI Centre for Research Training in Foundations of Data Science, and Human Health Institute. BSc in Computer Science MSc (Research) in Computer Science PhD in Computer Science Her research explores context-sensitive retrieval and evaluation methodology in AI-driven systems. Key areas include ubiquitous computing for personal data analysis, deep learning classification for mental wellness indicators, and multimodal lifelogging integration. Recent publications focus on urban mental wellbeing classification , contextual cue analysis , and AI-driven health search systems . Articles address smart city applications , consumer health search , and cross-lingual medical retrieval . Professional roles include Doctoral Consortium Chair at ECIR 2023 and Programme Committee member for SIGIR and ICWSM conferences. She leads grants for 4-year PhD studentships with stipend and fee coverage.

• Applied Artificial Intelligence
• Intelligent Search
• Ubiquitous Computing
• +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.

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

Assoc. Prof. Nhien An Le Khac is an Associate Professor at the School of Computer Science, University College Dublin. He serves as Programme Director for the MSc in Forensic Computing & Cybercrime Investigation, which has trained over 1,500 law enforcement officers globally. His research focuses on cybersecurity, digital forensics, AI security, and secure healthcare IT systems. He holds a PhD from Institut National Polytechnique de Grenoble (France) and has supervised 9 PhD students. His work includes pioneering contributions to electromagnetic side-channel analysis (EM-SCA) for IoT forensics, blockchain forensics, and AI-based fraud detection. Education: BSc/MSc: Vietnam National University, Ho Chi Minh City PhD: Institut National Polytechnique de Grenoble, France Professional Certificate in University Teaching & Learning: UCD Research Interests: Cybersecurity, Digital Forensics, AI Security, Machine Learning, Cloud Computing, Big Data Analytics, Healthcare IT Security. Recent Article Trends: Focus on EM-SCA for IoT device forensics, illicit Bitcoin transaction tracking, and cross-device ML portability. His work bridges theoretical AI advancements with practical forensic applications, emphasizing privacy preservation and explainable AI. Awards & Recognition: World’s Top 2% Scientists (2024) UCD Teaching Excellence Awards (2022, 2018) Best Paper Awards at Elsevier, AI-2022, and DFRWS conferences Grants & Advising: Principal Investigator on grants like Cloud Atlas, CERBERUS, and Urban ARK. Advised 9 PhD students who now work in academia/research globally. Active in funding initiatives like ML-Labs (SFI-funded). Labs & Teams: Leads ASEADOS Lab and maintains datasets like EM-SCA and InSDN. Collaborates globally on forensic frameworks and cybersecurity tools.

• Cybersecurity
• Digital Forensics
• AI Security
• +6 more

Rui Teixeira is an Assistant Professor in the School of Civil Engineering at University College Dublin (UCD). He leads UCD's Centre for Critical Infrastructure Research (CCIR) and focuses on Uncertainty Quantification, Safety, and Risk in civil engineering systems, with applications to infrastructure resilience. His research emphasizes reliability analysis, multi-fidelity modeling, and AI-driven risk assessment. Education: MSc in Civil Engineering, University of Porto, Portugal PhD in Civil Engineering, Trinity College Dublin Professional Certificate in University Teaching and Learning, UCD Research Interests: Development of novel reliability analysis techniques Resilience of infrastructure systems Artificial intelligence applications for risk assessment Probabilistic system evaluation and safety standards Grants & Projects: Smart Enforcement of Transport Operations (SETO), Horizon Europe (2023–2026) Optimality-Tracking Civil Engineering Systems, Enterprise Ireland (2023–2025) Floating Offshore Wind Dynamic Cables (FlOWDyn), Sustainable Energy Authority of Ireland (2024–2027) Teaching: Coordinates courses such as 'Civil Engineering Systems' and 'Design of Structures 1'. Labs/Teams: Director of the Centre for Critical Infrastructure Research (CCIR), focusing on interdisciplinary approaches to infrastructure resilience.

• Uncertainty Quantification
• Civil Engineering Systems
• Resilience Engineering
• +5 more

Usman Ali is an Assistant Professor and Adjunct Lecturer at the School of Mechanical and Materials Engineering, University College Dublin. He holds a Ph.D. in 'A data-driven GIS-based approach for multi-scale residential building energy modeling' (2020) from UCD and an M.Sc. in Computer Science from Lahore University of Management Science (2013). His research focuses on machine learning, GIS modeling, urban building energy systems, and energy performance certification. He has contributed to projects like the U.S.-Ireland R&D initiative on building stock classification and energy prediction, and collaborated with the Sustainable Energy Authority of Ireland (SEAI) on energy policy research. His work emphasizes data-driven solutions for energy efficiency, urban sustainability, and policy decision-making. Education: Ph.D., University College Dublin (2020) M.Sc., Lahore University of Management Science (2013) B.Sc., International Islamic University Islamabad (2008) Research emphasizes machine learning applications in energy modeling, GIS integration for urban planning, and energy policy frameworks. His recent work includes synthetic building datasets, occupancy-based energy analysis, and uncertainty quantification in energy systems.

• Machine Learning
• Data Mining
• GIS Modeling
• +4 more