Find Academic Supervisors

• 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.

• 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.

Muhammad Intizar AliView profile

Assistant Professor

• Data Analytics
• Internet of Things (IoT)
• Machine Learning & AI for IoT
• +8 more

Dr. Muhammad Intizar Ali is an Assistant Professor in the School of Electronic Engineering at Dublin City University (DCU). He holds a PhD (with distinction) from Vienna University of Technology, Austria (2011) and has held roles including Adjunct Lecturer and Research Fellow at the Insight Centre for Data Analytics, NUI Galway. His primary research focuses on IoT, Data Analytics, Machine Learning, and Knowledge Graphs with applications in Smart Cities, Manufacturing, Farming, and Healthcare. Education: PhD in Computer Science, Vienna University of Technology (2007-2011) Research Interests: IoT and Edge Analytics Federated and Distributed Machine Learning Semantic Web and Knowledge Graphs Smart Manufacturing and Industry 4.0 Stream Processing and Real-Time Systems Recent Work Trends: His publications emphasize federated learning frameworks, IoT-enabled adaptive intelligence, and knowledge graph applications in industrial contexts. Recent projects include digital twin systems for predictive maintenance and ontology-driven manufacturing solutions. Grants & Projects: Lead Investigator in SFI-funded projects like MultiRoof (2025-2029) and Neuro-Symbolic AI for Building Management EU/Industry collaborations including Terrain-AI and Bentley-funded initiatives Labs & Teams: Active in DCU's Data Analysis and Machine Learning research groups, leading projects like Smart DCU Digital Twin for campus optimization.

• Multi-Agent Systems
• Agent-Oriented Software Engineering
• Hypermedia Multi-Agent Systems
• +7 more

Rem Collier is an Associate Professor in the School of Computer Science at University College Dublin (UCD). He holds a PhD in Computer Science from UCD (2001) and has held academic roles including Assistant Lecturer (2004), College Lecturer (2005–2018), and his current position since 2018. His research focuses on Multi-Agent Systems (MAS), Agent-Oriented Software Engineering (AOSE), Hypermedia MAS, Digital Twins, and applications in smart agriculture and urban simulation. He leads the CONSUS project (2022–2024) and collaborates on CAMEO (2021–2024). Education: BSc (Pure/Applied Mathematics, University of Bristol, 1994), MSc (Computation, UMIST, 1995), MPhil (UMIST, 1996), PhD (UCD, 2001). Research interests include Agent Factory Framework, ASTRA programming language, and integrating MAS with microservices. Notable achievements include the CIA System Innovation Award 2003 (ACCESS architecture) and Best Paper Awards at EMAS2020 and Mobile Learning 2006. His work spans over 150 peer-reviewed publications and grants such as HOTAIR (2004–2005) and SIFT (2008–2011). Teaching includes modules on Multi-Agent Systems, Distributed Systems, and Security. He has coordinated courses at UCD and the Joint UCD-Fudan program in Beijing and Sri Lanka. Labs/Teams: Active in Hypermedia MAS Simulation, collaborating on projects like CONSUS and CAMEO, emphasizing smart agriculture and distributed knowledge graphs.

• 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.

• Cybersecurity
• Deep Learning
• Blockchain
• +7 more

Yuansong (John) Qiao is a Research Fellow at the Software Research Institute (SRI), Technological University of the Shannon: Midlands Midwest. His work spans cybersecurity, blockchain, and reinforcement learning, contributing to technologies like decentralized edge environments, intrusion detection systems, and immersive 360° video analytics. He supervises PhD students and actively explores applications in robotics, digital twins, and IoT. Recent publications highlight his focus on multi-view deep learning for anomaly detection , blockchain integration with AI , and ROS-based reinforcement learning . These works address challenges in cyber threat identification, decentralized finance, and smart manufacturing. His methodological innovations include knowledge graphs for security analytics and spatial audio analysis for VR environments. Qiao’s research aligns with UN Sustainable Development Goals, particularly in Quality Education (through supervised student projects) and Industry Innovation (via tools like Containerchain and UniROS). His collaborations span cybersecurity frameworks, decentralized robotics, and privacy-preserving systems for smart cities.

• Machine Learning
• Algorithm Engineering
• Combinatorial Optimization
• +3 more

Dr. Deepak Ajwani is an Assistant Professor in the School of Computer Science at University College Dublin . His research focuses on leveraging machine learning techniques for solving combinatorial optimization problems, with expertise in algorithm design, algorithm engineering, and graph algorithms. He holds a PhD from the University of Saarland, Germany, and has held postdoctoral positions at Aarhus University (Denmark) and University College Cork (Ireland). He also worked at Nokia Bell Labs (2012–2018) on learning systems for unstructured content analysis. Dr. Ajwani has received over 50 peer-reviewed publications in top-tier conferences and journals. He serves on the editorial board of the Machine Learning journal and is a frequent senior program committee member for conferences like WWW, IJCAI, AAAI, and ALENEX. He is a funded investigator at the SFI Centre for Research Training in Machine Learning (ML-Labs) . His teaching excellence has been recognized through multiple nominations for the UCD Teaching and Learning Award . His students have won the Franz Geiselbrechtinger Medal (2023, 2024) for best final-year projects in theoretical computer science. Key grants include the Irish Research Council and IBM Research Grant (2010–2012) for graph partitioning techniques in exascale computing. His research explores integrating machine learning with optimization algorithms, graph neural networks, and algorithm engineering for real-world applications.

Soumyabrata DevView profile

Assistant Professor

• Computer Vision
• Machine Learning
• Remote Sensing
• +6 more

Soumyabrata Dev is an Assistant Professor in the School of Computer Science at University College Dublin (UCD), where he leads the THEIA lab focusing on interdisciplinary research in computer vision, machine learning, and remote sensing. His work addresses challenges in climate science, environmental monitoring, solar forecasting, and healthcare. He holds a PhD from Nanyang Technological University (Singapore) and has held postdoctoral roles at Trinity College Dublin and ADAPT SFI Research Centre. His education includes a B.Tech. (summa cum laude) from National Institute of Technology Silchar, India, and a visiting doctoral experience at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. Prior to academia, he worked as a network engineer at Ericsson India (2010–2012). Research interests span image processing, environmental data analytics (e.g., air/water quality), solar energy forecasting, and AI-driven solutions for sustainable development. He collaborates globally with institutions in academia, industry, and government, aligning with UCD’s strategic goals for impactful innovation. He is an SFI Funded Investigator at ADAPT SFI and a UCD Climate Fellow (2024–2026). His scientific awards include the 2024 Stanford/Elsevier Top 2% Scientists List. He advises numerous PhD/MSc students on topics like coastal monitoring, air quality modeling, and AI for sustainability. THEIA Lab’s projects include solar irradiance forecasting, knowledge graph-based climate data platforms, and blockchain-enhanced healthcare systems. He teaches modules on Operating Systems, Wireless Sensor Networks, and Augmented/Virtual Reality. His work bridges theory and application, emphasizing real-world impact in climate action and renewable energy.

• Microfluidics
• Lab-on-a-Chip Technologies
• Biomedical Diagnostics
• +4 more

Prof. Jens Ducrée is a Full Professor of Microsystems in the School of Physical Sciences at Dublin City University (DCU). He is the founding director of FPC@DCU, Ireland’s first Fraunhofer Project Centre for Embedded Bioanalytical Systems, established with Science Foundation Ireland and Fraunhofer-Gesellschaft. He is also an academic member of the National Centre for Sensor Research (NCSR), the 3U Joint Institute of Global Health (JIGH), and a principal investigator at Biodesign Europe (BDE). His research focuses on microfluidic systems for bioanalytical protocols, with applications in biomedical diagnostics, environmental monitoring, biopharma, and agrifood. He explores blockchain integration to democratize science and RTD, leveraging technologies like AI and IoT. Education: Dr. Ducrée holds a Master’s and PhD in Physics. Prior to DCU, he was an Associate Professor and led groups at HSG-IMIT and the University of Freiburg’s IMTEK. Research Interests: Development of Lab-on-a-Chip platforms for automation and miniaturization of bioassays Microfabrication techniques for polymer-based systems Integration of disruptive technologies like blockchain, digital twins, and crowdsourcing into scientific workflows Scientific Awards: 2006 FAM-award for Microsystems Excellence (University of Freiburg) 2016 President’s Researcher of the Year (DCU) 2019 AET Fellow (International Academy of Engineering & Technology) Advising & Grants: Supervised 11 PhD, 28 MSc (Research), and 16 MSc (Taught) students, along with numerous undergraduate researchers. Secured over €60M in research funding, including €15M directly for his groups/centres. His work has led to patents, startups, and successful commercialization of microfluidic technologies. Labs/Teams: Directs FPC@DCU and collaborates with NCSR, JIGH, BDE, and international blockchain consortia (e.g., bloxberg, GBA). Active in ISO TC 307 mirror committees and Frontiers in Blockchain editorial roles.

• Digital Health Transformation
• E-Health Systems
• Natural Language Processing
• +3 more

Annette McElligott is an Associate Professor in the Department of Computer Science & Information Systems at the University of Limerick. Her work spans digital health transformation, eHealth systems, natural language processing (NLP), and cognitive styles in computer science education. She has contributed to multilingual ontology development, technical text analysis, and Irish-English language technology. Her research interests include systemic digital change in healthcare, the adoption of ePrescribing in primary care, and cognitive assessment of computer systems students. She has pioneered interactive approaches to multilingual concept ontologies and explored distributed representations for cross-lingual lexical analysis. Her publications range from foundational NLP work in the 1990s (e.g., software manual parsing using link parsers) to recent studies on digital health education programs. She has collaborated on projects involving the Princeton WordNet extension, industrial parsing frameworks, and Irish language computational tools. No scientific awards or active grants are explicitly listed in the provided materials. Her advising record remains unreported here. She maintains a focus on bridging technical communication, healthcare informatics, and language technology through interdisciplinary approaches.

Ali IntizarView profile

Assistant Professor

• Data Analytics
• Internet of Things (IoT)
• Stream Query Processing
• +3 more

Ali Intizar is an Assistant Professor at the School of Electronic & Computer Engineering , Dublin City University (DCU). Previously, he held roles as an Adjunct Lecturer, Research Fellow, and Research Unit Leader at the Data Science Institute, National University of Ireland, Galway. He earned his PhD (with distinction) in 2011 from Vienna University of Technology, Austria. Research interests: Ali specializes in Data Analytics , Internet of Things (IoT) , Stream Query Processing , Data Integration , Distributed and Federated Machine Learning , and Knowledge Graphs . His work applies these technologies to domains such as Smart Cities, Smart Manufacturing, Smart Farming, Environmental Monitoring, and e-Health. Funding & Collaborations: He has secured grants as principal investigator and funded investigator from the European Commission, Science Foundation Ireland, Enterprise Ireland, and industry partners. His research has resulted in over 100 publications in top-tier journals and international conferences. Education: PhD (with distinction), Vienna University of Technology, Austria (2011) Labs & Teams: Ali has contributed to the Data Science Institute at National University of Ireland, Galway, as a Research Unit Leader, and now collaborates with DCU's School of Electronic & Computer Engineering in advancing IoT and distributed machine learning applications.

Andy DonaldView profile

Research Fellow

• Artificial Intelligence
• Machine Learning
• Explainable AI
• +3 more

Andy Donald is a Research Fellow and lead of the Applied Innovation Unit at Insight, University of Galway. His work focuses on automating AI/ML processes, explainable AI methods, surrogate modeling for computational systems, and real-world applications in cloud environments. Research Expertise Explainability & Ethics in AI/ML Multimodal Data Applications High-Volume Stream Analytics Knowledge Graph Construction Surrogate Modeling Industry Collaboration Leadership Andy collaborates with industry partners including Fidelity , Genesys , Connacht Rugby , Avaya , and Aró Digital to bridge academic research with scalable solutions.

• Data Analytics
• Social Network Analysis
• Recommender Systems
• +4 more

Neil Hurley is an Associate Professor and Head of School in the School of Computer Science at University College Dublin. He holds a BSc and MSc from University College Dublin and a PhD from Trinity College Dublin. Before academia, he worked at the Hitachi Dublin Laboratory from 1989 to 1999, leading research in parallel computing and knowledge-based systems. He joined UCD in 1999 and founded the Information Hiding Laboratory in 2001, focusing on digital content security. His research spans recommender systems, social network analysis, high-performance computing, and data hiding technologies. He has secured over €1 million in research funding from agencies like Enterprise Ireland and the EU. His teaching includes coordinating modules on Artificial Intelligence, Recommender Systems, and Computational Science. He has reviewed for journals such as IEEE Transactions on Image Processing and serves on the EMPS Graduate School Board. His recent work emphasizes scalable recommendation algorithms, privacy-preserving distributed systems, and strategic network analysis.

• Agent-Based Modeling
• Multi-Agent Systems
• Computer Science Education
• +4 more

Seán Russell is an Assistant Professor in Computer Science at University College Dublin (UCD), affiliated with the School of Computer Science. He holds a BSc and PhD from UCD, as well as a Professional Diploma in University Teaching and Learning. His research spans agent-based simulation systems, multi-agent architectures, and computer science education. Notable contributions include work on hypermedia MAS, microservices for scalable simulations, and pedagogical strategies for non-native English speakers in CS1 courses. Education: BSc in Computer Science, University College Dublin PhD in Computer Science (details unspecified) Professional Diploma in University Teaching and Learning, University College Dublin Research Interests: Russell focuses on agent-oriented programming, distributed systems (microservices/REST), and innovative teaching methodologies. His work bridges theoretical agent architectures with practical applications like traffic simulation and waste management. Recent education-focused research addresses code quality in CS1, error message comprehension, and linguistic barriers for non-native English students. Grants & Awards: UCD College of Science Teaching Excellence Award (2022) OPTI-ROUTE Grant (2017–2018) Teaching & Learning Award (2021/2022) Teaching & Leadership: Coordinates modules in programming fundamentals (e.g., Intro to Programming 1, Object-Oriented Design) and serves as Vice Chair of the Ireland ACM SIGCSE Chapter. Supervised a PhD student (2019–2024).

Kevin MeehanView profile

Lecturer

• Computer Vision
• Machine Learning
• Ubiquitous Computing
• +3 more

Dr. Kevin Meehan serves as a Lecturer in Computing at Atlantic Technological University (ATU) in Ireland, holding dual roles as Principal Investigator for both WisarLab and the Centre for Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE). His academic foundation includes a BSc Hons and PhD in Computer Science from Ulster University, complemented by an MA in Learning & Teaching and a PGCE in Further and Higher Education. His research spans Computer Vision , Machine Learning , and Ubiquitous Computing , with significant contributions in trajectory prediction, immune response modeling, and environmental monitoring systems. Recent publications demonstrate expertise in BiLSTM networks, graph neural networks, and DenseNet applications for real-world problem solving. Notable professional recognition includes Fellowship in the Higher Education Academy. His work aligns with UN Sustainable Development Goals through technological solutions for health and environmental challenges. As an educator, he teaches Machine Learning, Computer Vision, and Data Science while leading industry collaborations with over 45 SMEs. His research has secured €400,000+ in funding for knowledge transfer projects, demonstrating strong industry-academia linkage.