جست‌وجوی استاد و پژوهشگر

• Microfluidics
• Lab-on-a-Chip Technologies
• Biomedical Diagnostics
• +۴ مورد دیگر

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

Martin Harriganمشاهده پروفایل

مدرس

• Blockchain
• Cryptocurrency Analysis
• Decentralized Finance (DeFi)
• +۳ مورد دیگر

Martin Harrigan is a Lecturer in the Department of Computing at South-East Technological University (SETU). His research focuses on blockchain technologies, decentralized systems, and privacy in cryptocurrency networks. He has contributed to studies on smart contracts, DAO governance mechanisms, and the analysis of protocols like Bisq and Ethereum. His work often intersects computer science, financial systems, and network analysis. Key research areas include blockchain architecture, tokenomics, and the privacy implications of decentralized platforms. Harrigan has published extensively on topics such as cross-blockchain analysis, address clustering techniques, and the structural patterns of networks like Wikipedia and social media. His findings have been presented at IEEE conferences and peer-reviewed journals. Notable projects include analyzing the privacy trade-offs in decentralized exchanges (e.g., Bisq), exploring token composition using EVM logs, and investigating voting mechanisms in DAOs. His work emphasizes practical applications of blockchain technology while addressing challenges in security, scalability, and anonymization.

• Artificial Intelligence
• Constraint Programming
• Optimization
• +۴ مورد دیگر

Professor Ken Brown is a faculty member at the Department of Computer Science, University College Cork (UCC), Ireland. He holds roles as Professor and Deputy Director of the Insight Centre for Data Analytics. His research focuses on Artificial Intelligence, constraint programming, optimization, and applications in wireless/sensor networks. He has led major projects including the Insight Centre (SFI), CTVR (telecom), and Authentic (energy management). Affiliations: Insight Centre, CTVR, GLACIATION, SEISMEC Key awards: IEEE SECON 2015 Best Demo, TAOS 2014 Best Paper Education: BSc (Mathematics, Glasgow), MSc (Logic & Computation, Manchester), PhD (AI in Engineering, Bristol). Extensive postdoc and academic roles at UCC, Aberdeen, and Carnegie Mellon. Research interests include constraint-based decision support, smart building systems, and network resilience. Over 150+ publications in journals like Ad Hoc Networks , Constraints , and conferences like IEEE SECON, ICTAI. Grants: Over €10M secured, including SFI, EI, and ERC funding. Supervised 30+ PhD/MSc students. Current research includes smart energy systems, autonomous network repair, and AI for emergency response.

• Additive Manufacturing
• Polypropylene
• Heat Transfer Analysis
• +۶ مورد دیگر

David Tormey is a Senior Lecturer and Director of the Precision Engineering Materials and Manufacturing Research Centre (PEM Research Centre) at Atlantic Technological University's Department of Mechanical & Manufacturing Engineering. His research focuses on additive manufacturing, heat transfer optimization, and advanced materials processing, particularly in polypropylene and stainless steel applications. He leads interdisciplinary projects addressing sustainable manufacturing and industrial innovation. Research interests include additive manufacturing techniques, laser welding of polymers, computational fluid dynamics (CFD), and sensor integration for real-time process monitoring. His work contributes to UN Sustainable Development Goals related to Industry, Innovation, and Infrastructure (SDG 9) and Climate Action (SDG 13). Recent studies emphasize roughness effects on heat transfer in additive-manufactured channels, optimization of injection molding processes, and biomedical applications of nanocoatings. Collaborations span academic and industrial partners globally, addressing challenges in energy-efficient manufacturing and materials science. The PEM Research Centre, under his leadership, develops cutting-edge solutions for precision engineering and advanced manufacturing systems. His publications (58+ articles) highlight contributions to thermal engineering, polymer processing, and AI-driven quality control in manufacturing.

Muhammad Yahyaمشاهده پروفایل

پژوهشگر

• Optical Network-on-Chip (ONoC)
• Cybersecurity
• Heuristic Optimization Algorithms
• +۲ مورد دیگر

Muhammad Yahya is a researcher at Nanjing University of Aeronautics and Astronautics with affiliations to institutions like Universiti Malaysia Terengganu and Norwegian University of Life Sciences. His work bridges optical network-on-chip (ONoC) and cybersecurity domains. H-index: 21 Total citations: 1,400+ Research Interests: Focus on photonic interconnects for manycore processors, heuristic optimization algorithms for crosstalk reduction, and security vulnerabilities in optical networks. Key projects include: Designing non-blocking optical switches with reduced power consumption Developing DPA-resistant cryptographic architectures for lightweight ciphers Creating heuristic fusion mapping algorithms combining PSO and SA Publication Trends: Recent articles (2018-2023) demonstrate expertise in optical router design , fault analysis of encryption protocols, and machine learning applications to network optimization. Technical Contributions: Invented the PSO_SA algorithm for crosstalk optimization, HoneyComb ROS reconfigurable switches, and two-domain MATLAB frameworks for computational mathematics.

• Digital Health Transformation
• E-Health Systems
• Natural Language Processing
• +۳ مورد دیگر

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

Ali Intizarمشاهده پروفایل

استادیار

• Data Analytics
• Internet of Things (IoT)
• Stream Query Processing
• +۳ مورد دیگر

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

• 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 .

Devishree Pillaiمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Devishree Pillai is a Research Assistant at the Insight Centre for Data Analytics at the University of Galway, working under the supervision of Dr. Paul Buitelaar. She collaborates with industry leaders such as Fidelity Investments, Accenture, and Huawei Technologies on advanced research projects. Current focus: Enhancing question-answering capabilities of large language models (LLMs) using domain-specific knowledge graphs Past projects: Dependency parsing-based relation extraction for Fidelity Investments, multilingual social media analysis for the EU-funded PANDEM-2 project, and integration of LIME-based explainable AI (XAI) techniques into intent classification models for Huawei Technologies Research Interests include: Natural Language Processing (NLP) Explainable AI (XAI) for model transparency Knowledge Graph integration with language models Fake News Detection using deep learning architectures Education : Master's in Data Analytics (2021) from University of Galway Bachelor's in Computer Science Engineering from Mumbai University

Simon Sarkarمشاهده پروفایل

پژوهشگر

• Data Analytics
• Natural Language Processing
• Machine Learning
• +۳ مورد دیگر

Simon Sarkar is a Researcher at the Insight Centre for Data Analytics within the University of Galway. His work focuses on explainable AI systems, particularly knowledge graph-based recommendation systems for the Fidelity project (Phase 5, Work Package 2), and semantic similarity analysis for user queries in collaboration with Huawei. Education: MSc in Data Analytics from National College of Ireland (2020) Bachelor’s in Computer Applications Research interests include Knowledge Graphs , Natural Language Processing , Reinforcement Learning , and Machine Learning , with a focus on optimization in continuous action spaces and HR analytics applications. Labs/Teams: Insight Centre for Data Analytics Unit for Natural Language Processing (supervised by Dr. Paul Buitelaar)

• 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.

• Machine Learning
• Deep Learning
• Recommender Systems
• +۷ مورد دیگر

Dr. Ruihai Dong is an Assistant Professor at the School of Computer Science, University College Dublin, affiliated with the Insight Centre for Data Analytics. His research bridges Machine Learning, Deep Learning, and Recommender Systems with significant applications in finance and medical imaging. Develops AI-driven solutions for financial markets and healthcare Collaborates with industry partners like Eagle Alpha and Samsung Funded by Enterprise Ireland for commercialization studies Research focuses on: Recommender systems (news, finance, conversational AI) Graph neural networks for financial risk modeling Medical imaging under limited labeling constraints Algorithmic transparency and ethical AI applications 3D CNNs & transformers for seismic analysis Large language models for multilingual evaluation Recent publications emphasize: Hybrid architectures for multimodal data Explainable AI techniques in financial and news domains Geometric deep learning for microstructure and seismic data Curriculum strategies in active learning Media bias mitigation frameworks Latent space modeling for asset embeddings Scientific contributions recognized through: Outstanding Research Award 2018 by UCD School of Computer Science Industry collaborations include work with: Eagle Alpha (financial analytics) SkillPages (data-driven platforms) Samsung (technology innovation)

Andy Donaldمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence
• Machine Learning
• Explainable AI
• +۳ مورد دیگر

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

• Sustainable Orchestration in Edge-Cloud Environments
• Multi-Cloud Workload Distribution
• Large Language Models (LLMs) Deployment
• +۳ مورد دیگر

Dr. Hadi Tabatabaee Malazi is an Assistant Professor at the University of College Dublin (UCD), leading the Sustainable Orchestration in Computing Continuum (SOC² Lab). He holds an Orcid identifier (0000-0002-2960-6896) and has extensive academic experience across institutions like Maynooth University, Shahid Beheshti University, and Trinity College Dublin. His research focuses on sustainable computing, edge-cloud continuum orchestration, AI/ML deployment (e.g., LLMs), and energy efficiency. He is a Senior Member of IEEE, serves as an Associate Editor for IEEE Access, and chairs the COST Action CA22151 (CYPHER) on decarbonizing energy-intensive industries. Education: PhD (2012): University of Isfahan (Computer Engineering) MSc (prior to 2012): University of Isfahan Research Visit (2010-2011): Delft University of Technology Research Interests: Sustainable edge-cloud systems, AI-driven workload optimization, carbon-aware resource management, distributed LLMs, and IoT interoperability. Key contributions include over 20 journal articles in IEEE, Elsevier, and Springer venues, with topics ranging from vehicular network security to smart city event processing. Professional Activities: Committee member of COST Action CA22151, IEEE Access Associate Editor, and Technical Program Committee member for IEEE conferences. Authored certifications on research leadership and research integrity from Epigeum. Labs/Teams: SOC² Lab (UCD), leading projects on edge-cloud sustainability and AI application deployment.

• Data Analytics
• Social Network Analysis
• Recommender Systems
• +۴ مورد دیگر

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