Find Academic Supervisors

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

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

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

• Machine Learning
• Artificial Intelligence
• Virtual Reality
• +3 more

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.

• Soil Science
• Climate Change Mitigation
• Environmental Protection
• +5 more

Dr. Sharon O'Rourke is an Assistant Professor and Ad Astra Fellow at the University College Dublin (UCD) School of Biosystems and Food Engineering since 2019. Previously, she held roles at the University of Sydney and UCD's School of Agriculture and Food Science, focusing on soil science and environmental protection. She holds a BAgrSc from UCD and a PhD in Soil Nutrient Management from Queen's University Belfast. Research Interests: Her work centers on sustainable soil management, soil carbon sequestration, and environmental protection. She employs spectral techniques (e.g., mid-infrared, hyperspectral imaging) and modeling to study soil geochemistry, carbon dynamics, and climate change mitigation. Current projects include ClimateCropping (EU-wide soil carbon management), PRISM (in-field soil sensors), and CFunction (carbon-nutrient stoichiometry). Grants & Projects: Key grants include funding from Teagasc, the Department of Agriculture, and the Sustainable Energy Authority of Ireland. Notable projects include proximal soil sensing for carbon monitoring and bio-based product development via pyrolysis. Teaching: She coordinates modules such as 'Carbon & Sustainability,' 'Soil Technology,' and 'Research Skills,' emphasizing agricultural systems and climate-smart practices. Awards: Recognized as an Ad Astra Fellow, highlighting her contributions to innovative soil science research.

• Machine Learning
• Time Series Analysis
• Text Mining
• +7 more

Dr. Georgiana Ifrim is an Associate Professor at the School of Computer Science, University College Dublin , where she serves as Director of Graduate Research and Co-Lead of the SFI Centre for Research Training in Machine Learning (ML-Labs). She holds concurrent appointments as an SFI Funded Investigator at the Insight Centre for Data Analytics and VistaMilk SFI Research Centre . Her academic journey includes postdoctoral research at Insight Centre, Cork Constraint Computation Centre (4C), and Aarhus University's Bioinformatics Research Centre (BiRC). Education: BSc in Computer Science, University of Bucharest, Romania MSc and PhD in Informatics, Max-Planck Institute for Informatics, Germany Dr. Ifrim specializes in scalable predictive modeling for diverse applications including: Sequence learning (DNA analysis, time series) Real-time prediction for streaming data (news/social media, energy) Interpretable machine learning models Knowledge graph exploitation (WordNet/Yago, Naga) Wearable sensor data analysis (sports science, health monitoring) Energy price forecasting for sustainable systems Her recent publications focus on time series explainability (TSHAP, tsCaptum), multivariate analysis (scalable channel selection), and healthcare applications (fall detection, walking speed estimation). Key contributions include open-source tools like SEQL (sequence learner) and Twitter-Topics (event detection). Scientific Awards: Winner of SNOW@WWW14 Data Challenge As Director of Graduate Research, she oversees advanced academic training while leading funded projects at the intersection of machine learning , real-time analytics , and domain-specific applications in agriculture, healthcare, and digital journalism. Her research group maintains active GitHub repositories with open-source implementations.

Mathieu MercadierView profile

Assistant Professor

• Business Analytics
• Machine Learning
• Statistics
• +4 more

Dr. Mathieu Mercadier is an Assistant Professor of Business Analytics at Dublin City University Business School, Ireland. He serves as Programme Chair for the MSc and Graduate Diploma in Business Analytics. His research focuses on Business Analytics, Machine Learning, Financial Risk Management, and Sustainable Finance. Education: PhD in Economics from Université de Limoges, France, specializing in Machine Learning applied to Banking and Finance. He has ten years of industry experience as a Market Finance Consultant. Research interests include applying Machine Learning to banking risk, sustainable finance, and quantitative finance. His work spans statistical modeling for financial stability, algorithmic risk assessment, and ESG fund evaluation. Key trends in his articles involve quantum-enhanced machine learning for stock forecasting, systemic risk measurement, and pandemic impact analysis. No scientific awards listed. Advising and grants: No formal grants or student advisees mentioned. Active in curriculum development for business analytics programs. Engaged in international conferences and seminars. Labs/Teams: Not explicitly stated in provided data.

• 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.

• Artificial Intelligence
• Machine Learning
• Medical Imaging
• +4 more

Prof Noel O'Connor is a Full Professor at Dublin City University's School of Electronic Engineering, specializing in cutting-edge research at the intersection of artificial intelligence (AI), medical imaging, robotics, and smart city technologies. His work spans applications such as cardiac MRI reconstruction, robotic manipulation using reinforcement learning, and the development of the Smart DCU Digital Twin for autism-friendly university environments. Research interests include AI-driven medical diagnostics, multimodal data fusion, and adaptive systems. His contributions to cardiac MRI reconstruction and transformer-based medical imaging analysis reflect a strong focus on healthcare innovation. He also explores ethical AI practices to reduce social bias in foundation models. Recent work emphasizes smart infrastructure projects, such as optimizing parking recommendations for electric vehicles and enhancing accessibility through digital twin frameworks. His research often integrates real-time sensor data and multi-agent systems to address complex urban challenges. No scientific awards are listed. Collaborations include the ASU-DCU International Research Program on Sensors and Machine Learning. Advising details and grant information are not explicitly provided.

• Machine Learning
• Interactive Machine Learning
• Healthcare Applications
• +5 more

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

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.

Sabin TabircaView profile

Senior Lecturer

• Artificial Intelligence
• Data Analytics
• Algorithmics
• +6 more

Dr. Sabin Tabirca is a Senior Lecturer at the School of Computer Science and Information Technology, University College Cork (UCC). He holds a BSc from Bucharest University and a PhD from Brunel University. His research focuses on Artificial Intelligence, Data Analytics, Algorithmics, Interactive Media, and HCI, with applications in computational cancer modeling, mobile health (mHealth), and parallel computing. He coordinates MPT Activities and is affiliated with the CRR Group and BCRI Centre. Notable awards include UCC's President Award for Innovation in Teaching (2007), IT@Cork Leader Award (2008), and UCC Staff Recognition Award (2013). His teaching includes modules like Parallel and Grid Computing, Mobile Application Design, and Graphics for Interactive Media. Dr. Tabirca has supervised over 70 MSc students and numerous PhD candidates, many of whom now hold academic and industry roles globally. His research includes developing mHealth apps for cystic fibrosis patients, 3D cancer visualization tools, and frameworks for mobile parallel computing. Publications span mHealth design pipelines, cancer prediction models, and mobile gaming for health education. He actively engages in interdisciplinary projects, blending computer science with medical and biological applications.

Gregorio IglesiasView profile

Professor

• Marine Renewable Energy
• Coastal Engineering
• Wave Energy Conversion
• +5 more

Prof. Gregorio Iglesias is a Professor of Marine Renewable Energy at University College Cork (UCC) and Honorary Professor of Coastal Engineering at the University of Plymouth. His expertise lies in Marine Renewable Energy and Coastal Engineering, with a focus on wave and tidal energy systems, offshore wind integration, and coastal protection strategies. He has secured over €12M in research funding as Principal Investigator and authored/edited key texts such as Wave and Tidal Energy (Wiley) and Ocean Energy and Coastal Protection (Springer). Education: BEng (Civil Engineering, 1992), MEng (Civil Engineering, 1993), PhD (Engineering, 2001). Research Interests: Advanced modeling of wave energy converters, floating offshore wind turbines, coastal erosion mitigation, and climate change impacts on marine energy resources. His work bridges theoretical advancements and practical applications, including coasts like the Port of Gijón (Spain) and the Shannon Estuary. Recent publications highlight climate-driven renewable energy transitions, multi-hazard coastal resilience frameworks, and techno-economic assessments of offshore systems. He chairs the IEC Standards panel for wave energy device testing and serves as Subject Editor for Energy (Elsevier) . Professional Activities: Lead of Marine Renewable Energy research at MaREI (Ireland), former Head of the COAST Engineering Group at Plymouth (2012–2018), and member of PIANC’s Universities Consortium. His work has generated 5,459 citations with an h-index of 41. Teaching: Delivers modules on Ocean Energy (NE4003/NE6005) and Hydraulics (CE3007).

Paul LeahyView profile

Lecturer

• Wind Energy
• Renewable Energy
• Circular Economy
• +4 more

Dr. Paul Leahy is a Lecturer in Wind Energy Engineering at University College Cork (UCC) and a funded investigator in the SFI MaREI Centre for Energy, Climate, and Marine Research. He leads research on wind energy, circular economy applications for decommissioned turbine blades, and climate change impacts. His work includes the Re-Wind project, a transdisciplinary initiative funded by SFI, NSF, and Northern Ireland's Department for the Economy. He co-supervises six PhD students and has examined over 20 theses globally. Education: BE Electrical Engineering (1995), PhD Electrical Engineering (2001), Postgraduate Certificate in Teaching & Learning in Higher Education (2018). Research & Awards: Research focuses on wind energy forecasting, energy storage, and greenhouse gas emissions. Notable awards include the Environmental Research Letters' 2013 Highlight and an ISI Highly Cited Paper (2012). He contributed to IPCC Special Reports on climate change mitigation and co-edits Renewable & Sustainable Energy Reviews. Grants & Projects: Secured €320,000 for Re-Wind and led multiple EU, EPA, and industry-funded projects. Current research includes lifecycle assessments of repurposed turbine blades and hydrogen production via offshore wind. Teaching & Outreach: Coordinates modules like NE6003 Wind Energy Engineering and contributes to energy systems education. Engages in public lectures and policy initiatives like Energy Cork Cluster leadership. Labs & Teams: Collaborates with multidisciplinary teams on infrastructure repurposing (e.g., BladeBridges) and climate adaptation strategies for agriculture and peatlands.

Ali NazarpourView profile

Assistant Professor

• Operations and Supply Chain Management
• Artificial Intelligence
• Mass Customization
• +4 more

Dr. Ali Nazarpour is an Assistant Professor in Management at the School of Business, Maynooth University. He holds a PhD in Operations and Supply Chain Management from University College Dublin’s Smurfit School of Business, along with a BSc in Industrial Engineering and an MSc in Business Administration from Iran University of Science and Technology. Prior to his academic career, he spent nine years in industry roles, including Sales Supervisor, Marketing and Sales Planning Chief, and Inventory Management Project Manager in the automotive sector, alongside teaching and research activities. His work bridges industry experience with academic rigor, focusing on supply chain optimization, mass customization strategies, and AI integration in business processes. Education: PhD in Operations and Supply Chain Management (Smurfit School of Business, UCD) MSc in Business Administration (Iran University of Science and Technology) BSc in Industrial Engineering (Iran University of Science and Technology) Research Interests: Artificial Intelligence applications in supply chain and logistics Mass customization feasibility across industries and countries Third-party logistics selection methodologies Project management and risk mitigation strategies Global logistics frameworks Industry 4.0 technologies for operational efficiency His publications and conference contributions between 2014 and 2021 highlight trends in leveraging AI for supply chain decision-making, analyzing mass customization challenges, and exploring cross-country operational dynamics. Despite no explicit scientific awards listed, his active participation in conferences like INFORMS, POMS, and EurOMA underscores his academic engagement. In advising and teaching, he focuses on Contemporary Issues in Management, Operations and Supply Chain Management metrics, and Project Risk Management. His industry experience enriches classroom discussions and research projects. He is based in the TSI Building (Room 253) and reachable via ali.nazarpour@mu.ie or phone (01) 474 7516.