جستجوی استاد راهنمای دانشگاهی

• Information Retrieval
• Interactive Information Retrieval
• Personalisation
• +۴ مورد دیگر

Ralf Bierig joined Maynooth University's Computer Science Department in 2017, teaching topics including information retrieval, software testing, interaction design, and virtual reality. He is the programme director of the Higher Diploma in Human-Computer Interaction (HCI) and User Experience (UX). He earned his BSc (2002) from University of Furtwangen and PhD (2008) from Robert Gordon University. Research Interests His work spans information retrieval, interactive information retrieval, personalisation, information search behavior, usability (UX), and virtual reality (VR). Recent publications focus on multimodal concept indexing, hybrid IR approaches, and contextual adaptation in search systems. Publication Trends His research combines statistical semantics, graph modeling, and multimodal data analysis across academic collaborations in Austria, Germany, and international venues like ECIR and SIGIR.

Arash Joorabchiمشاهده پروفایل

استادیار

• Machine Learning
• Natural Language Processing
• Educational Technology
• +۴ مورد دیگر

Arash Joorabchi is an Assistant Professor at the Department of Electronic and Computer Engineering, Faculty of Science and Engineering, University of Limerick, Ireland. His research focuses on the intersection of machine learning, educational technology, and digital library systems, with particular emphasis on automated assessment, text mining, and knowledge organization techniques. Research Trends: Analysis of his publications reveals sustained contributions to automated short-answer grading, Arabic text classification, and semantic integration of Wikipedia with academic resources. Key methodologies include sentence transformers, hybrid text representation models, and citation-based indexing techniques. Technical Domains: His work spans natural language processing, educational data mining, metadata management, and semantic web technologies. Specific applications include Q&A platform analysis, library resource discovery, and curriculum development systems.

• Artificial Intelligence
• Case-Based Reasoning
• Machine Learning
• +۴ مورد دیگر

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
• +۳ مورد دیگر

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.

• Cybersecurity
• Digital Forensics
• AI Security
• +۶ مورد دیگر

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.

• Topology
• Algebra
• Mathematical Physics
• +۳ مورد دیگر

Florian Naef is an Assistant Professor in the School of Mathematics at Trinity College Dublin. His research spans topological and algebraic structures with applications to mathematical physics, including string topology, Poisson geometry, and homotopy theory. Publications emphasize formality theorems, torsion invariants, and quantization methods. Recurring themes include loop spaces, deformation quantization, and connections between differential geometry and algebraic topology.

• Machine Learning
• Time Series Analysis
• Text Mining
• +۷ مورد دیگر

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.

• Artificial Intelligence
• Machine Learning
• Medical Imaging
• +۴ مورد دیگر

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.

Muhammad Intizar Aliمشاهده پروفایل

استادیار

• Data Analytics
• Internet of Things (IoT)
• Machine Learning & AI for IoT
• +۸ مورد دیگر

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.

• Data Governance
• AI Ethics
• Data Protection
• +۴ مورد دیگر

Dr. Rob Brennan is an Assistant Professor in the School of Computer Science at University College Dublin. With 25 years of academic and industry experience, he specializes in data governance, AI ethics, and cybersecurity. His research integrates socio-technical systems analysis, data protection frameworks, and healthcare risk management. He leads the Value and Risk research challenge within the ADAPT Centre's Transparent Digital Governance initiative and coordinates projects like the ARK platform for risk governance. Education: BSc in Physics, Dublin City University MSc, Queen's University Belfast PhD in Governance, Dublin City University Professional Diploma in University Teaching and Learning, University College Dublin Research Interests: Data Governance & AI Accountability GDPR Compliance & Privacy Engineering Healthcare Risk Management Knowledge Graphs & Linked Data Cybersecurity & Incident Response Key Contributions: Co-PI of Science Foundation Ireland's Empower Data Governance project Coordinator of the €4M H2020 ALIGNED project on software/data engineering Developed the ARK platform for risk governance in healthcare and cybersecurity Grants & Awards: Best Paper Award at Extended Semantic Web Conference 2023 Principal Investigator for grants including the ARK-Virus platform (SFI-funded) Teaching & Mentorship: Coordinates courses on Cyber Risk Assessment, Incident Response, and Data Protection Supervises PhD students focusing on data governance and AI ethics Co-developed the MA in Data Protection and Privacy Law with Computing Professional Activities: Member of FAccT 2023 Program Committee Co-chair of the Irish Conference on Artificial Intelligence and Cognitive Science Contributor to international standards (OMG, IETF, 3GPP)

• Transfer Learning
• Recommender Systems
• Medical Imaging
• +۳ مورد دیگر

Honghui Du serves as a Research Fellow at the Insight Centre for Data Analytics, a leading Irish research institution specializing in data science with nodes across multiple universities. The role centers within the Decision Making research group, focusing on algorithmic solutions for dynamic environments. Research spans transfer learning in non-stationary data streams , recommender systems (notably news personalization using LLMs and diffusion models), and medical imaging under label scarcity. Key emphases include handling concept drift, optimizing active learning for medical diagnostics, and developing generative approaches for user-item interaction modeling. Emerging work explores gamification for sustainable behavior change and entity resolution via language models. Recent publications (2023-2025) reveal accelerating integration of diffusion models and transformers into recommendation frameworks, while maintaining core expertise in transfer learning for evolving data streams. Medical imaging research increasingly addresses practical constraints like limited annotations through adaptive curriculum strategies. The work operates within the Decision Making research group at the Insight Centre, which investigates algorithmic decision processes under uncertainty and dynamic conditions.

Tai Tan Maiمشاهده پروفایل

استادیار

• Data Mining
• Learning Analytics
• Process Mining
• +۳ مورد دیگر

Dr. Tai Tan Mai is an Assistant Professor at Dublin City University's School of Computing. He holds a PhD from DCU funded by the Irish Research Council and an MSc in Business Information Systems from University College Cork (2016) where he graduated as top-performing student. His research integrates data mining, learning analytics, and complex systems theory with applications in educational technology and business process management. Research interests focus on: Educational data mining and learning analytics Cryptocurrency market analysis using graph-based methods AI applications in education and societal risk assessment Complex systems approaches to programming education Prior to academia, he developed Business Process Management solutions for Vietnam's banking/financial sector.

Sampritha Hassan Manjunathمشاهده پروفایل

پژوهشگر ارشد

• Ontology Learning
• Knowledge Graph Generation
• Relation Extraction
• +۳ مورد دیگر

Sampritha Hassan Manjunath is a Research Fellow at the Insight Centre for Data Analytics at the University of Galway, working under Prof. Paul Buitelaar in the Unit for Natural Language Processing (UNLP). Her primary focus includes ontology learning, knowledge graph generation, relation extraction, named-entity recognition, text analysis, and information extraction. MSc in Artificial Intelligence, University of Galway Her research integrates domain-specific knowledge to advance natural language processing (NLP) tasks, with industry collaborations involving Huawei, the EU, Tr3dent, and the University of Galway on projects like intent classification and automatic SDG mapping. Sampritha has published papers on knowledge graph tools and deep learning models for term recognition, leveraging BERT embeddings and the EEAP framework. She is affiliated with the Insight Centre for Data Analytics and previously gained software engineering experience at Intel Technologies and CGI Group Inc., specializing in Java, Agile, Scrum, and CI/CD practices.

• ontologies
• lexicography
• knowledge graphs
• +۵ مورد دیگر

John McCrae is a lecturer at the Insight Centre for Data Analytics, University of Galway, Ireland. He works within the Unit for Natural Language Processing under Paul Buitelaar, focusing on linguistic linked open data and lexical resource modeling via lemon and OntoLex frameworks. Research Focus: ontologies, lexicography, knowledge graphs, machine translation, linked data, machine learning, under-resourced languages, digital humanities Funding: €1.7m from EU, IRC, SFI Collaborations: Fidelity Labs, Standardization with W3C and OASIS His publications address code-switching datasets, machine translation for Dravidian languages, ontology lexicons, and taxonomy extraction. He organized the Linked Data in Linguistics workshop series and the 2017 Language, Data and Knowledge (LDK) conference. Scientific Awards: IRC Consolidator Laureate Awards (2017/2018)

• Machine Learning
• Computer Vision
• Human Motion Analysis
• +۳ مورد دیگر

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.