Zohreh Pourzolfaghar is an Assistant Professor in Management Information Systems (MIS) at the School of Business, Maynooth University (MU). She serves as Director of the IT-Enable Innovation Programme and cluster lead for the Digital Construction cluster at the Innovation Value Institute (IVI). She is also a member of Lero, the SFI Research Centre for Software. Education: PhD in Project Management (University Putra Malaysia, 2011); MSc in Management Systems and Productivity; BSc in Software Engineering. Research Interests : Focuses on digital transformation for SMEs, information management in construction, and smart city architectures. Leads EU-funded projects like EnTrust (agri-data governance), DIGI+ (sustainable digital transformation), and DigiFABs (food & beverage SMEs). Co-PI for projects such as GDI-IE (genomic data infrastructure) and PERFORM (digital retail innovation). Grants & Awards : Secured funding from SFI, Enterprise Ireland, and EU. Notable awards include the BIM Hero Award (2022) and Research Engaged Award (2022). Teaching : Courses include Digital Business, Digital Technology Governance, and Enterprise Architecture. Advises PhD students in MIS and digital transformation. Industry Collaboration : Works with firms like ArcDox and Corballis Technologies on BIM standards and data governance. Active in national and EU policy networks, including NSAI committees.
Dr. Andrew Hines is a Researcher at the School of Computer Science, University College Dublin, specializing in machine learning applications for signal processing in speech, audio, and video domains. His work focuses on Quality of Experience (QoE) modeling, speech quality assessment, and immersive media analysis. He has held leadership roles in European COST Actions like Qualinet and CryptoAction, and previously worked in industry as a Director of Engineering. University: University College Dublin Role: Director of Research, Innovation and Impact Key Collaborations: IEEE (Senior Member), Audio Engineering Society (Ireland) Research interests center on machine learning for QoE optimization, audio-visual integration, and healthcare applications like heart sound classification and stroke rehabilitation. His recent publications explore self-supervised learning, neural speech codecs, and contextual factors in speech/audio quality assessment. Scientific contributions include awards like IEEE Senior Membership, and his work spans both academic research and industrial engineering in finance and aviation sectors. He leads the QxLab research team at UCD and develops open-source platforms such as WARP-Q and AQP for quality metrics.
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).
Ciarán Mac an Bhaird is an Associate Professor of Business and Management at Dublin City University (DCU), within the Fiontar & Scoil na Gaeilge department. He holds a PhD from Trinity College Dublin, a B.Comm and LL.B from NUI Galway, and an M.Sc. in Finance from DCU. His academic role includes teaching and supervising PhD students focusing on enterprise policy, high-growth firm financing, and entrepreneurship education. Research interests span resourcing small firms, capital structure, alternative finance, and public policy for SMEs. He authored Resourcing Small and Medium Sized Enterprises (Springer-Verlag, 2010), launched by the Irish Minister for Enterprise. His work has been published in journals like Small Business Economics and Venture Capital . He chairs the Entrepreneurial Finance track at the Institute of Small Business and Entrepreneurship Conference and serves as an associate editor for Research in International Business and Finance . Current PhD advisees include Simon Bridge, Nouf Alnasser, Batoul Batoulbanjar, and Sean O Reilly. Professional activities include contributions to policy reports for Enterprise Ireland and the Irish League of Credit Unions, and participation in the U.S. State Department’s International Visitor Leadership Programme.
Dr. Vivek Nallur is an Assistant Professor in the School of Computer Science at University College Dublin. His research focuses on Machine Ethics, Multi-Agent Systems, emergence in socio-technical systems, and decentralized adaptation mechanisms. He holds a PhD from the University of Birmingham and advanced certifications in university teaching from UCD. Education: BBS, Delhi University Post-Graduate Diploma in Advanced Software Technology, National Centre for Software Technology MS, Carnegie Mellon University PhD, University of Birmingham Prof Cert University Teaching & Learning, University College Dublin Research Interests: Machine Ethics explores ethical decision-making in autonomous systems, while Multi-Agent Systems (MAS) are his primary tool for studying self-adaptation and emergence. He serves on key committees like IEEE P7008 (Ethically Driven Nudging) and the AAAI 2021 Spring Symposium on AI Ethics. His work bridges computer science with philosophy, law, and social sciences. Advising & Grants: Supervises three PhD students focusing on ethical AI, elder-care robotics, and AI governance. Leads the Machine Ethics Research Group and participates in the ML-Labs SFI grant (2019–2027). Professional Roles: Senior Member of IEEE, organizer for AAAI ethics symposia, and contributor to OpenAAL's ELSI panel. Teaches modules on Machine Learning, Operating Systems, and Web Development.
Katarina Domijan is an Associate Professor in Statistics at the Department of Mathematics and Statistics, Maynooth University, Ireland. She holds a PhD in Statistics from Trinity College Dublin (2008) and has been affiliated with Maynooth University since 2008, transitioning from Lecturer/Assistant Professor to her current role in 2024. Her academic career includes editorial roles as Associate Editor for The R Journal (2021–present) and the Journal of Computational and Graphical Statistics (2015–2024). Research Interests focus on Bayesian methods for high-dimensional data, particularly in classification problems. She specializes in feature selection and model visualization, with applications spanning agricultural data analysis (e.g., hyperspectral imaging for lactose prediction), medical diagnostics (e.g., sepsis and cancer detection), and space physics (e.g., Saturn Kilometric Radiation classification). Her work bridges theoretical statistics with real-world challenges, including socio-economic studies and forensic science. Key Research Areas Bayesian statistical inference Machine learning for large feature spaces Statistical computing and model interpretability Data visualization and chemometrics Scientific Contributions include leading projects like VistaMilk Phase II (2024–2030, €152,300) and Measuring Carbon Sequestration (2024–2028, €174,788.90). Her 15 most recent publications highlight advancements in ensemble modeling, spatial statistics, and medical diagnostics. Scientific Awards Associate Editor, The R Journal (2021–present) Associate Editor, Journal of Computational and Graphical Statistics (2015–2024) Student Supervision includes PhD and MSc graduates such as Dr. Bruna Wundervald (2024) and Dr. Mark O’Connell (2017). She also collaborates with researchers across disciplines, including Dr. Nadim Akasheh in food hypersensitivity studies.
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.
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.
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.
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.
Alan Duggan is a Research Fellow in the Department of Building & Civil Engineering at the University of Galway, affiliated with the Engineering Research Group (ERG). His work focuses on sustainable construction practices, environmental engineering, and the environmental impact of infrastructure projects, particularly in peatland regions. He specializes in carbon footprint analysis, geotechnical challenges in peatland construction, and the development of low-carbon materials and techniques. Principal Investigator in ERG Focus areas: Peatland rehabilitation, carbon sequestration in construction materials, and sustainable transportation infrastructure His research integrates geotechnical engineering with environmental science, addressing challenges in ground improvement, drainage systems, and carbonation processes. Key contributions include studies on stabilized peat as a carbon sink and embodied carbon analysis in motorway construction. His publications span environmental sustainability, material science, and infrastructure planning, emphasizing practical solutions for reducing environmental impact in construction projects.
Simon Colreavy Donnelly is an Associate Professor in the Department of Computer Science & Information Systems at the University of Limerick. He is a member of the Interaction Design Centre and focuses on interdisciplinary research at the intersection of artificial intelligence, educational technology, and healthcare informatics. His work spans machine learning applications in medical data analysis, virtual reality (VR) and extended reality (XR) for inclusive education, and deep learning techniques in chemical analysis and spectroscopy. Research Interests: His primary areas of investigation include generative AI for education equity, semisupervised learning algorithms, virtual learning environments design, and the ethical deployment of immersive technologies in healthcare and palliative care. He also explores NMR spectroscopy analysis using deep learning and develops tools for nutritional content estimation through image processing. Collaborations: His recent collaborations span international teams addressing challenges in toxicity-free online discourse (PAN 2024), semisupervised learning distribution mismatches, and VR applications for post-pandemic blended learning. His work integrates computational methods with real-world applications in education, healthcare, and chemical analysis. Labs/Teams: Active within the Interaction Design Centre at UL, his research group develops practical solutions for accessibility in digital education and healthcare systems, emphasizing user-centered design principles for extended reality applications.
Michael P. O'Brien is an Associate Professor of Information Management at the Department of Management & Marketing, Kemmy Business School, University of Limerick. He teaches undergraduate and postgraduate modules in Information & Knowledge Management, Business Analytics Simulation, and Technical Communication, serving as Course Director for the MA in Business Management programme. PhD in Computer Science (University of Limerick) MSc in Computer Science (by research and thesis, University of Limerick) BSc (Hons) in Information Systems His research bridges Data Analytics , Software Evolution , and Educational Psychology , focusing on empirical studies of programmers, instructional design, and gamification in education. Recent publications explore experiential learning and gamification for strategic thinking . Michael supervises Masters students in topics ranging from Cloud Computing Security to Blockchain in Finance , with a focus on Big Data and AI Impacts . His advising style emphasizes practical applications and technology-driven solutions. 2000 : AGB Dwyer Memorial Award for Excellence in Education 2017 : KBS Seed Funding Competition He actively contributes to academic networks like the Irish Learning Technology Association and Psychology of Programming Interest Group , aligning his work with UN Sustainable Development Goals.
Constantine Evans is a Research Fellow at the Hamilton Institute, Maynooth University, focusing on the physics of complex self-assembly processes. His work examines how simple particles organize into intricate structures through algorithmic self-assembly, with applications in DNA nanotechnology and computational modeling. Institution: Maynooth University Research Unit: Hamilton Institute Location: Eolas Building, 3rd Floor, Office 339 Research Interests: Evans investigates non-equilibrium self-assembly systems, particularly DNA tile crystal growth and kinetic control mechanisms. His research bridges physics, computational theory, and molecular engineering to uncover unexpected behaviors in basic physical processes. Publication Trends: His recent work (2018-2024) demonstrates interdisciplinary advancements in DNA computing, focusing on proofreading systems, tile compiler optimization, and kinetic modeling. These publications span peer-reviewed journals, conference proceedings, and algorithmic frameworks that connect theoretical computer science with experimental biophysics. Labs & Teams: He is affiliated with the Hamilton Institute, a research center specializing in systems biology, computational modeling, and interdisciplinary scientific investigations.
Dr. Barry Cardiff is an Assistant Professor in the School of Electrical and Electronic Engineering at University College Dublin (UCD), where he has been a member of academic staff since September 2013. His career spans both industry and academia, with significant experience at Nokia Mobile Phone (UK) Ltd and Silicon & Software Systems (S3 group) before returning to complete his PhD at UCD. Education: B.Eng (1992), M.Eng.Sc. (1995), PhD (2011) from University College Dublin Professional Experience: Design Engineer at Nokia (1993-2001), Systems Architect at S3 group (2001-2007, 2011-2013) Current Position: Assistant Professor at UCD School of Electrical and Electronic Engineering Dr. Cardiff's research focuses on Digital Signal Processing applications in communication systems, with particular emphasis on theoretical analysis and practical implementation. His work bridges traditional communication theory with emerging biomedical applications, especially in wearable IoT sensors. He has made significant contributions to power/complexity reduction techniques in circuit design, specifically DSP algorithms for digitally assisted analog circuits. His research program addresses critical challenges in biomedical signal processing, sensor fusion, and efficient data transmission for healthcare applications. His recent publications demonstrate a strong trend toward biomedical applications of signal processing techniques, with a focus on ECG analysis, atrial fibrillation detection, and respiratory rate estimation using multimodal sensor fusion. The research shows a clear progression from traditional communication systems toward healthcare applications, with an emphasis on edge computing solutions that reduce power consumption in wearable devices. IEEE BioCas best paper award (2024) IEEE senior member since 2019 Active reviewer for multiple IEEE journals including Transactions on Biomedical Circuits and Systems, Circuits and Systems, and VLSI Systems Dr. Cardiff has supervised numerous research projects and has been instrumental in developing curriculum for digital communications, signal processing, and wireless systems. His teaching philosophy emphasizes open, friendly, and hands-on approaches that encourage independent thinking. He coordinates multiple modules including Communication Theory, Digital Electronics, DSP Technology, and Wireless Systems, demonstrating his commitment to both theoretical foundations and practical applications of electrical engineering principles. His research group works at the intersection of signal processing, machine learning, and biomedical engineering, developing innovative solutions for wearable healthcare monitoring. Current projects focus on event-driven processing architectures, decentralized classification systems, and signal quality-aware fusion techniques that enable robust performance in noisy real-world environments.
