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Romina GaburroView profile

Associate Professor

• Inverse Problems
• Partial Differential Equations
• Imaging and Material Properties Identification
• +7 more

Romina Gaburro is an Associate Professor at the University of Limerick's Department of Mathematics and Statistics, with affiliations including the Centre for Research Training in Foundations of Data Science, the Centre for Sustainable Digital (Re)Manufacturing, and the Mathematics Applications Consortium for Science and Industry (MACSI). She serves as Director for Postgraduate Studies, Course Director for the MSc in Mathematical Modelling, and Research Representative for the Science and Engineering Faculty Research Committee. PhD, Mathematics, University of Manchester Institute of Science and Technology (UMIST) MSc, Mathematics, Università degli Studi di Trieste Her research focuses on inverse problems, partial differential equations (PDEs), and their applications to imaging and material properties identification. Key applications include geophysics (e.g., oil reservoir detection), medical imaging (e.g., tumor identification), and nondestructive testing (e.g., material defect detection). Recent publications highlight advancements in anisotropic conductivity reconstruction, singular solution analysis, and stability theory for boundary value problems. Her work intersects disciplines like seismic imaging, diffuse optical tomography, and smart manufacturing. She received the 2023 Simons Foundation Fellowship and UL President's 2022 Outstanding Research Collaboration Award. Gaburro actively promotes gender balance in STEM as Irish ambassador for the IMU Committee for Women in Mathematics and co-founder of ICEDIM.

Saim GhafoorView profile

Lecturer

• Terahertz Communications
• Intelligent Radio Communications
• Green Machine Learning
• +7 more

Saim Ghafoor is a Lecturer in the Department of Computing at Atlantic Technological University, Ireland. He holds a PhD in Engineering and Technology from University College Cork (2018), an MEng from Hanyang University (2010), and a BEng in Computer Systems Engineering from Mehran University (2005). His research focuses on advanced wireless communications, including Terahertz networks, green machine learning, and emergency communication systems. He is actively involved in the review process of top-tier journals and conferences. Education: PhD, University College Cork, 2018 MEng, Hanyang University, 2010 BEng, Mehran University, 2005 His work spans Terahertz communications , intelligent radio systems , and 5G/6G network protocols , with contributions to cybersecurity and automation. Notable outputs include a 2023 book on Green Machine Learning Protocols and a 2020 IEEE Communications Surveys review on Terahertz MAC protocols. He leads the WiSAR research group and serves as Associate Editor for Elsevier's Computers & Electrical Engineering . Grants & Labs: Active in the WiSAR (Wireless Sensor Applied Research Gateway) unit at ATU. Collaborates on projects involving THz networks and disaster response systems.

Michael BreenView profile

Associate Professor

• International Political Economy
• Corruption Studies
• International Financial Institutions
• +3 more

Dr. Michael Breen is an Associate Professor in the School of Law and Government at Dublin City University, part of the Faculty of Humanities & Social Sciences. He specializes in international political economy, focusing on power dynamics within international financial institutions and the socio-economic impacts of corruption. His research spans over 30 peer-reviewed articles and two books, addressing topics such as IMF governance, regulatory evasion, and corruption in public infrastructure. He co-directs DCU’s Anti-Corruption Research Centre (ARC) and advises the European Commission’s DG Home Affairs on anti-corruption strategies. Notable roles include presenting at the UN and European Commission, as well as supervising numerous PhD students and postdoctoral researchers. Dr. Breen has secured significant research funding from bodies like the Irish Research Council and Enterprise Ireland, leading projects on governance reform and financial stability. His work bridges theoretical frameworks with applied policy analysis, emphasizing the interplay between institutional structures and real-world outcomes. Key themes include regulatory compliance in multinational corporations, crisis management in disaster contexts, and transparency in global financial systems.

Abdul ShahidView profile

Lecturer

• Data Science
• Large Language Models (LLMs)
• Applied Artificial Intelligence
• +12 more

Dr. Abdul Shahid is a Lecturer in Business Information Systems at the School of Business, South East Technological University (SETU), Waterford campus. He holds a PhD in Computer Science from Capital University of Science and Technology, Islamabad, and has previously served as a Lecturer at the National College of Ireland and a Postdoctoral Researcher at the University of Galway, contributing to EU Horizon 2020 projects such as Polifonia and InsiDE PRI. Research Interests: Dr. Shahid's research lies at the intersection of data science, large language models (LLMs), scientometrics, and applied AI. His work emphasizes the development of intelligent systems for decision-making in logistics, cybersecurity, and semantic computing. He is particularly focused on citation analysis, contextual embeddings, and the deployment of Retrieval-Augmented Generation (RAG) frameworks in industrial applications. Recent Research Trends: His recent publications reflect a strong emphasis on natural language processing for scientific literature analysis, including in-text citation identification, intent classification, and semantic modeling. These works integrate machine learning with knowledge engineering to extract and structure scientific knowledge from academic texts. Scientific Awards: No specific awards mentioned in the provided text. Advising and Grants: Dr. Shahid is currently accepting PhD students. His research has been supported through participation in high-impact EU-funded projects such as Horizon 2020’s Polifonia and InsiDE PRI, which involved data-driven analysis of scientific collaboration and knowledge graph applications in cultural heritage. Labs and Research Teams: He has been affiliated with research teams at the University of Galway working on EU Horizon 2020 initiatives. At SETU, he contributes to research in applied AI and business information systems, particularly in developing intelligent solutions for logistics and document understanding.

• Theoretical Physics
• Computational Physics
• Biological Physics
• +7 more

Nicolae-Viorel Buchete is an Associate Professor of Theoretical & Computational Nano-Bio Physics at University College Dublin's School of Physics within the College of Science. He currently serves as Vice Principal for Graduate Studies for the College of Science and Director of the UCD MSc in Computational Physics Programme. His academic journey includes postgraduate degrees from Boston University (USA) and institutions in the EU (Al. I. Cuza University of Iasi, Romania, and the University of Patras, Greece), with a PhD from Boston University and research fellowships at the National Institutes of Health. His educational background includes: PhD from Boston University Research Fellowships at National Institutes of Health (Bethesda, MD, USA) Postgraduate degrees from Boston University, Al. I. Cuza University of Iasi (Romania), and University of Patras (Greece) Buchete's research focuses on theoretical and computational approaches to understanding biomolecular systems. His work spans theoretical and computational biological physics, chemical physics, and nanoscience , with specific emphasis on statistical mechanics and molecular dynamics of biomolecular systems, systems biology, structural bioinformatics, and multiscale modeling of biomolecules and complex fluids. His group employs advanced computational techniques including Markov State Models, Milestoning, and replica exchange molecular dynamics to study protein conformational dynamics, amyloid formation, and molecular mechanisms relevant to diseases like cancer and Alzheimer's. His research output reveals a progression from fundamental biophysics toward increasingly translational applications. Early work focused on protein conformational dynamics, while more recent publications demonstrate expansion into nanomedicine applications, computational toxicology of nanomaterials, and physics-based modeling frameworks for drug delivery systems. A significant portion of his research involves studying conformational transitions in proteins relevant to cancer (such as K-Ras4B and Abl kinase) and neurodegenerative diseases (particularly amyloid systems), with growing emphasis on computational approaches to nanosafety and sustainability. His scientific contributions have been recognized with numerous awards: Certificate of Appreciation from the American Chemical Society Publications Division (2012) Top 20 JCP Reviewer for 2010 from the American Institute of Physics NIH Fellows Award for Research Excellence (FARE) in 2006 and 2007 ACS Chemical Computing Group Excellence Award (2003) Multiple teaching and research awards from Boston University including the Outstanding Teaching Fellow Award (1998) and Feldman Award (2001) Buchete has mentored numerous graduate students through their MSc and PhD research, with students successfully defending theses on computational physics and biomolecular modeling topics. His teaching philosophy emphasizes "research-oriented teaching," integrating research experiences into undergraduate and taught Master's level education. He has secured research funding including the UCD OBRSS Research Support Scheme (2016-2023) and has directed multiple educational programs including the UCD International Pre-Masters Programme (2013-2022) and served as School Head of Teaching and Learning (2021-2022). His research group is affiliated with the UCD Complex & Adaptive Systems Laboratory (CASL), where they develop and apply advanced computational methods to study complex biomolecular systems. The group has organized multiple CECAM workshops on biomolecular modeling and simulations, demonstrating leadership in the computational biophysics community. They collaborate extensively across disciplines, working with experimentalists to validate computational findings and address challenging problems in biophysics and nanomedicine.

Viet Quoc PhamView profile

Assistant Professor

• Edge Computing
• Edge AI
• Aerial Computing
• +11 more

Viet Quoc Pham is an Assistant Professor in Networks and Distributed Systems at Trinity College Dublin's School of Computer Science and Statistics and a CONNECT Associate Investigator. His research integrates convex optimization, game theory, and machine learning to advance edge computing, wireless AI, and next-generation networking for 6G, IoT, and blockchain applications. Education: PhD in Telecommunications Engineering, Inje University, Korea (2017) His work centers on three interconnected thrusts: (1) Computing innovations in edge AI, aerial computing, and edge of things; (2) Intelligence through wireless AI and federated learning; and (3) Networking advancements in 6G, IoT, intelligent surfaces, metaverse, and blockchain. This cross-disciplinary approach optimizes cloud-edge systems and wireless infrastructure using mathematical frameworks. Recent publications (2021-2024) demonstrate applied impact across security (smart speaker intrusion detection), environmental science (satellite carbon monitoring), healthcare (mental disorder detection), and e-commerce (basket recommendation systems), reflecting his methodology of adapting AI/optimization to domain-specific challenges. Scientific Awards: Korea NRF funding for outstanding young researchers (2019-2024) Best Ph.D. Dissertation Award, Inje University (2017) Top Reviewer Award, IEEE Transactions on Vehicular Technology (2020) Golden Globe Award, Vietnam Ministry of Science (2021) IEEE ATC Best Paper Award (2022) Enterprise Ireland Coordination Support Award (2023) Dr. Pham secured competitive funding including Korea NRF and Enterprise Ireland grants. As Editor for Journal of Network and Computer Applications and Scientific Reports, and Lead/Guest Editor for IEEE Internet of Things Journal, IEEE Transactions on Consumer Electronics, and Computer Communications, he shapes discourse in networking and computer systems through rigorous peer review and special issues. Through the CONNECT Centre, he collaborates with industry partners on Ireland's national research initiative for future networks, focusing on practical implementations of 6G architectures, IoT security protocols, and edge AI frameworks for real-world deployment.

• Structural Dynamics
• Structural Health Monitoring
• Renewable Energy
• +5 more

Dr. Vikram Pakrashi is an Associate Professor in Mechanical Engineering and Director of the Dynamical Systems and Risk Laboratory (DSRL) at University College Dublin. He specializes in structural dynamics, structural health monitoring (SHM), vibration control, and renewable energy systems. His work bridges industry and academia, focusing on infrastructure resilience and emerging technologies. Education: BEng (1st Class Hons) from Jadavpur University; PhD from Trinity College Dublin. Research interests include dynamical systems, risk analysis, and smart structures. He leads interdisciplinary projects funded by industry and agencies like SEAI and the EU. Recent research trends emphasize renewable energy infrastructure (e.g., offshore wind, wave energy devices) and innovative SHM techniques using machine learning and sensor networks. His articles highlight advancements in wave measurement, defect detection algorithms, and structural fragility analysis. Awards: Engineering Laboratory of the Year 2018 (Irish Laboratory Awards). Grants: Includes projects like SISdATA (Atlantic aquaculture systems) and FlOWDyn (dynamic cable analysis for floating offshore wind). Lab Leadership: Directs DSRL, fostering industry collaboration and applied research.

• Performance Engineering
• Telecommunication Systems
• Enterprise Software
• +3 more

John Murphy is a Full Professor at the School of Computer Science, University College Dublin. He holds academic positions as an IBM Faculty Fellow and Fellow of multiple professional organizations, including the Institution of Engineering and Technology and Engineers Ireland. His research focuses on Performance Engineering, Telecommunication Systems, and Middleware, with a strong emphasis on cloud computing, distributed systems, and network optimization. Education: B.E. (Electronic Engineering) from University College Dublin (1988), M.Sc. (Electrical Engineering) from California Institute of Technology (1990), and Ph.D. (Electronic Engineering) from Dublin City University (1996). Research Interests: His work spans Performance Engineering, Telecommunication Systems, Enterprise Software, Middleware, Mobile Networks, and Queueing Theory. Notable contributions include energy-efficient cloud resource management and network-aware scheduling in data centers. Publications: Over 200 peer-reviewed articles, including recent work on intelligent computing in IoT, energy-efficient VM mapping, and load balancing in wireless networks. His research trends emphasize cloud optimization, distributed systems performance, and smart city infrastructure. Awards: Recognitions include the Real Time Correlation Engine award and prestigious fellowships. He has supervised 24 PhD students and secured over €9.5M in research grants. Teaching: Coordinates modules on Computer Networking, Databases, and Programming. He advocates for foundational learning to foster adaptability in students. Grants: Includes Horizon 2020 projects like NEO-QE and PRTLI grants for SimSci. Collaborates with industry partners for applied research. Labs: Leads the Performance Engineering Laboratory, advancing research in distributed systems and network performance.

• Machine Learning
• Computer Vision
• Human Motion Analysis
• +3 more

Dr. Timilehin Aderinola is a Marie Curie Postdoctoral Fellow at the School of Computer Science, University College Dublin. His research focuses on applying machine learning and computer vision to analyze human movement, particularly in neurological conditions like Parkinson's disease. He holds a PhD in Information Technology from Multimedia University, Malaysia (2022), and master's and bachelor's degrees from Federal University of Technology Akure, Nigeria (2017 and 2012). Education: B.Eng. (Hons) in Electrical and Electronic Engineering, Federal University of Technology Akure (2012) M.Sc. in Computer Science, Federal University of Technology Akure (2017) PhD in Information Technology, Multimedia University Malaysia (2022) Research Interests: Machine Learning and Computer Vision Human Motion Analysis (e.g., gait analysis, fall detection) Applications in healthcare and surveillance Awards: Silver Medal (2021) for commercialization potential of PhD work Honourable Mention (2021) at NP2C poster competition Advising/Grants: Co-supervised research projects on exercise classification and human pose estimation. Engaged in peer review for conferences like ECML-PKDD and ICoICT. Labs/Teams: Active in the Insight Centre for Data Analytics at UCD, focusing on NeuroInsight Marie Skłodowska-Curie Fellowship projects analyzing mobility data for neurological patients.

• 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.

• Artificial Intelligence
• Natural Language Processing (NLP)
• Machine Learning
• +6 more

Dr. Rejwanul Haque is a Lecturer in the Department of Computing at South East Technological University (SETU), Carlow, Ireland. He holds a PhD in Computer Science and Engineering from Dublin City University (DCU), where he was supported by an SFI PhD Fellowship (2008–2011). His career spans industry and academia: he contributed to MT systems at Lingo24 and Applied Language Solutions, developed cloud-based MT solutions like SmartMATE, and led industry-oriented research at ADAPT Centre for Huawei Noah’s Ark. He was a Research Fellow at ADAPT (2019–2021) with Marie Sklodowska-Curie Fellowship funding, and Programme Director for MSc AI at National College of Ireland (2020–2022). His research focuses on AI, NLP, and machine translation challenges, including low-resource translation, ethical MT use, and adaptive systems. He has published 70+ peer-reviewed papers and collaborates with institutions like DCU, Trinity College Dublin, and French universities. He currently supervises two PhD students at SETU and secured funding for SETU’s PhD programme. Education: PhD in Computer Science and Engineering (Dublin City University, 2011) Research Interests: Dr. Haque’s work addresses cutting-edge NLP topics such as interactive machine translation, fairness in AI, domain adaptation, and sustainable MT models. He explores applications in biomedical translation, social media analytics, and question-answering systems. His recent projects include developing adaptive MT systems using large language models and improving low-resource language translation through novel techniques. Grants & Collaborations: He secured €189,924 via a Marie Sklodowska-Curie Fellowship and attracted SETU PhD scholarships (2023–2024). Collaborators include Microsoft Ireland, ADAPT Centre, and researchers from University Saint-Etienne, La Rochhelle University, and TCD. His work on the Citizen’s Assembly for COVID-19 earned the ADAPT Recognition Award (2020). Labs/Teams: Active contributor to the ADAPT Centre’s NLP initiatives and collaborates with DCU’s MT group. Engages in cross-institutional projects with French academic partners to advance multilingual systems and ethical AI practices.

Liting ZhouView profile

Assistant Professor

• Multimedia Retrieval
• Natural Language Processing
• Peer Learning
• +3 more

Dr. Liting Zhou is an Assistant Professor at Dublin City University's School of Computing, specializing in multimedia retrieval and information systems. She completed her PhD in Computer Science at DCU under Dr. Cathal Gurrin's supervision, focusing on multimedia analysis. Her research develops algorithms for video understanding, multimodal learning, and lifelog retrieval applied to education, healthcare, and personal informatics domains. Key research areas include: Cross-modal video-text matching and retrieval Lifelog question answering systems Multimodal fusion techniques User-friendly retrieval interfaces She serves as reviewer for top conferences/journals and has chaired sessions at MMM (2023-2024) and ECIR (2023).

James PattenView profile

Research Fellow

• Machine Learning
• Software Engineering
• Source Code Analysis
• +3 more

James Patten is a Research Fellow at the University of Limerick , affiliated with the Department of Computer Science & Information Systems and the research center Lero – the Irish Software Research Centre . His work focuses on applying machine learning and evolutionary computation to enhance software quality, with a specific emphasis on code duplication detection and refactoring. Primary Affiliation: Department of Computer Science & Information Systems, University of Limerick Research Center: Lero – the Irish Software Research Centre Patten’s research spans two major domains: Software Engineering: Code duplication elimination, clone detection using BERT-based models, evolutionary algorithms for codebase analysis Gender Equity: Active participant in the WiSTEM2D initiative, exploring systemic interventions to improve female representation in STEM fields His publications reflect a dual focus on scalable software analysis techniques (e.g., ensemble inference for clone detection) and social science studies on gender dynamics in technology education. Notably, Patten combines technical rigor with societal impact by addressing both software reliability and diversity challenges.

• International and Comparative Politics
• European Union Policy-Making
• Natural Language Processing in Political Analysis
• +7 more

James Cross is an Associate Professor in the School of Politics and International Relations at University College Dublin (UCD) and serves as the Director and co-founder of the Connected_Politics Lab @ UCD. His position places him at the intersection of political science and data analytics, where he applies computational methods to study EU political processes and decision-making. Dr. Cross received his BA from University College Cork, an MSc in International Relations from the University of Bristol, and completed his PhD at Trinity College Dublin. His postdoctoral work included positions at the ETH in Zurich and as a Max Weber and Jean Monnet Fellow at the European University Institute in Florence. Cross's research agenda focuses on international and comparative politics, with particular emphasis on EU policymaking processes. He has pioneered the application of natural language processing techniques to analyze large corpora of legislative texts in the EU, developing innovative methods to examine patterns of conflict and cooperation between EU institutions. His work extends beyond the EU context, with methodological approaches adaptable to other legislative bodies worldwide. His research spans several interconnected themes: data science applications in EU politics, legislative amendment tracking, transparency in EU decision-making, and the Decision-Making in the EU (DEU) project. Cross frequently employs computational methods including text analysis, network analysis, and machine learning to extract meaningful insights from political texts and communications. His publication record demonstrates a consistent trajectory of innovative research applying computational methods to political science questions, particularly concerning EU institutions. Cross's work shows a strong emphasis on methodological innovation alongside substantive contributions to understanding EU legislative processes, transparency mechanisms, and institutional dynamics. His recent publications increasingly focus on central banking communications, algorithmic bias in political analysis, and the application of network approaches to understanding policy agenda dynamics. PSAI Teaching and Learning prize (2021) European Union Politics/SAGE Award for best article (2018) Nomination for best conference paper (2015) Visiting Scholar fellowship at the University of Milan (2015) Jean Monnet Chair (2019-2022) Cross has secured multiple research grants including the Jean Monnet Chair, the EUR_data project integrating EU studies with data analytics, the ParliView project bridging information divides, the SDG_EU project tracking sustainable development goals' influence, and the EU Data Laboratory project. He actively engages in teaching innovation, with course syllabi openly shared on GitHub, and coordinates modules including Advanced Seminar in Politics, AI and Large Language Models, EU Foreign Policy, Introduction to EU Politics, and Politics of (mis-)information. As Director of the Connected_Politics Lab, Cross leads a research environment at the intersection of political science and data analytics. The lab collaborates with the Insight Centre for Data Analytics at UCD and focuses on applying computational methods to political texts and processes. His work has established him as a key figure in the application of data science to EU politics, with particular expertise in analyzing legislative processes and political communications through computational approaches.

• Speech Recognition
• Artificial Intelligence
• Pattern Recognition
• +3 more

Michael Russell is a Lecturer in the Faculty of Engineering and Informatics, Department of Computer and Software Engineering. His academic career spans over three decades, with active research contributions from 1988 to the present. He specializes in interdisciplinary fields blending technical innovation with pedagogical exploration. Research interests include Speech Recognition, Artificial Intelligence, and Pattern Recognition. Notable work involves intelligent agents, data mining, and applying artificial life principles to speech processing systems. His educational research focuses on software engineering curriculum design, tacit knowledge integration, and team-based learning strategies. Publications reflect a dual focus on advancing technical domains like speech enhancement algorithms and educational methodologies. Recent works emphasize curriculum design and team-based learning, while earlier contributions include foundational research in distributed operating systems and early AI models. No scientific awards were listed in the provided information. Advising and grants details are currently unavailable. No specific lab affiliations or teams are mentioned.