جستجوی استاد راهنمای دانشگاهی

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.

• 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.

• Multi-Agent Systems
• Agent-Oriented Software Engineering
• Hypermedia Multi-Agent Systems
• +۷ مورد دیگر

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.

• 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.

Abdul Shahidمشاهده پروفایل

مدرس

• Data Science
• Large Language Models (LLMs)
• Applied Artificial Intelligence
• +۱۲ مورد دیگر

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.

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.

John Breslinمشاهده پروفایل

استاد

• Data Science
• Artificial Intelligence
• Social Semantics
• +۷ مورد دیگر

John Breslin is a Personal Professor in Electronic Engineering at the University of Galway, leading the TechInnovate/AgInnovate programs. His roles include Director of the Insight (Data Analytics) and VistaMilk (AgTech) research centers. He has authored 350+ publications and co-created the SIOC framework, widely used in web applications. His research spans Data Science, AI, Semantic Web, IoT, and Entrepreneurship. He has won multiple awards, including the Best Irish-Published Book and IIA Net Visionary Awards. His teaching spans 25 years, covering topics like Digital Control Systems and Innovation. He co-founded boards.ie, StreamGlider, and leads initiatives in Galway's innovation ecosystem. Research Interests: Data Science, AI, Social Semantics, IoT, Agricultural Technology, and Innovation. He is ranked top in Engineering and Computer Science citations at the University of Galway. His work contributes to UN SDGs related to Industry, Innovation, and Infrastructure. Education: Details not explicitly provided in text. Collaborations include Bosch, Cisco, IBM, and Harvard Medical School. Active in industry partnerships and startups, including the PorterShed Innovation District. Awards: Best Paper Awards, Entrepreneurship Recognition, and Academic Excellence. Supervised nearly 30,000 ECTS across modules, with a focus on graduate and postgraduate tech innovation programs.

Derek Bridgeمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Data Analytics
• Algorithmics
• +۳ مورد دیگر

Dr. Derek Bridge is a Senior Lecturer in the School of Computer Science and Information Technology at University College Cork (UCC). His research focuses on Artificial Intelligence, Data Analytics, and Algorithmics, with particular expertise in Recommender Systems and Case-Based Reasoning. He has led multiple research projects funded by organizations like Science Foundation Ireland (SFI) and the Environmental Protection Agency (EPA), exploring topics such as waste exchange optimization and collaborative recommendation systems. Dr. Bridge holds a PhD from the University of Cambridge and a BSc from Brunel University. His work spans over three decades, with significant contributions to academic journals and conferences, including top-tier venues like ACM Recommender Systems and International Conferences on Case-Based Reasoning (ICCBR). He has organized conferences such as the Workshop on Reasoning from Experiences on the Web (WebCBR) and served on editorial boards, including the ACM Transactions on Interactive Intelligent Systems . Research Interests: - Recommender Systems (diversity, serendipity, and beyond-accuracy objectives) - Case-Based Reasoning (CBR) applied to problem-solving and explanation generation - Machine Learning and Optimization (ant colony algorithms, collaborative filtering) - Applications in e-commerce, music recommendation, and decision support systems Awards: 2010 BCS SGAI Paper Award 2010 ICTAI Best Paper Prize 2004 ICCBR Best Paper Prize 2014 Crowd Favourite Award (Computer Cooking Contest) Teaching & Professional Activities: - Supervised PhD students (e.g., Walid Trabelsi, Lisa Cummins) - Served as external examiner for institutions in Ireland, Portugal, Spain, and beyond - Reviewed proposals for funding agencies in Ireland, Italy, and France

• Machine Learning
• Algorithm Engineering
• Combinatorial Optimization
• +۳ مورد دیگر

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.

• Artificial Intelligence
• Deep Learning
• Machine Learning
• +۱۷ مورد دیگر

Majjed Al-Qatf is a Researcher at the University of Galway , collaborating with Prof. Edward Curry. His work focuses on data spaces, knowledge graphs for data sharing, large language models, and retrieval augmented generation for question answering. Education: B.S. in Network Technology and Computer Security (Sana’a University, 2013), M.S. in Computer Science and Technology (Central South University, 2019), Ph.D. in Computer Science and Technology (University of Science and Technology of China, 2023) His research spans artificial intelligence, particularly deep learning , machine learning , NLP , and computer vision , with applications in network intrusion detection , image captioning , activity recognition , and explainability . Prior work includes image enhancement , knowledge graphs , and federated learning . Publications appear in journals such as IEEE Transactions on Multimedia , ACM Transactions on Multimedia Computing, Communications and Applications , and conferences like the IEEE International Conference on Big Data and International Conference on Software and Computer Applications .

• Natural Language Processing
• Knowledge Extraction
• Semantic-based Information Access
• +۱۲ مورد دیگر

Paul Buitelaar is a Professor in Data Analytics and Deputy Director of the Data Science Institute at the University of Galway. He leads the Multimodal Data Analysis research program through the Insight SFI Research Centre for Data Analytics, focusing on Natural Language Processing (NLP) for knowledge extraction and semantic information access. Co-Director of SFI Centre for Research Training in AI Co-PI of Insight SFI Research Centre for Data Analytics Collaborates with industry partners like Fidelity Investments, Huawei, and Irish Times His research spans ontology learning, linguistic linked data, and social media analysis, particularly in legal and healthcare domains. He developed the Saffron framework for knowledge extraction and contributed to EU-funded projects such as Monnet and MixedEmotions. His publications emphasize NLP applications in legal text analysis, taxonomy generation, and health content categorization. Projects like Pret-a-LLod and MixedEmotions highlight his interdisciplinary approach combining NLP with computer vision and sensor analysis. Paul's work integrates knowledge graphs and back-translation techniques to enhance machine translation, alongside unsupervised methods for analyzing social media health data.

• Agent-Based Modeling
• Multi-Agent Systems
• Computer Science Education
• +۴ مورد دیگر

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).

Alessandra Mileoمشاهده پروفایل

دانشیار

• Stream Reasoning
• Neurosymbolic AI
• Explainable AI
• +۳ مورد دیگر

Alessandra Mileo is Associate Professor and Data Science Programme Chair at Dublin City University's Faculty of Engineering and Computing. As a Principal Investigator at the Insight SFI Research Centre for Data Analytics, her research focuses on neurosymbolic AI, explainability, and representation learning. Education includes an M.Sc. and Ph.D. in Computer Science from the University of Milan. Current research investigates methods combining knowledge-driven and data-driven AI approaches to enhance explainability and reduce bias in machine learning systems. Research leadership includes EU projects like CityPulse (IoT stream processing) and industry collaborations on Internet of Everything infrastructures. Teaches data science courses and supervises multiple PhD students.