جستجوی استاد راهنمای دانشگاهی

David Lillisمشاهده پروفایل

دانشیار

• Natural Language Processing
• Artificial Intelligence
• Digital Forensics
• +۴ مورد دیگر

David Lillis is an Associate Professor in the School of Computer Science at University College Dublin (UCD). His research focuses on Natural Language Processing (NLP), Artificial Intelligence (AI), and their applications in legal and forensic contexts. He leads projects like CeADAR (Ireland’s Applied AI Center) and the Transpire project, collaborating with organizations such as Corlytics and the Department of Enterprise, Trade and Employment. He holds adjunct roles as a Guest Professor at Beijing University of Technology’s Data Mining and Security Lab and has been a Fulbright Scholar at the University of New Haven’s Cyber Forensics Research and Education Group. Education: B.A. (Hons) in Law and Accounting, University of Limerick Higher Diploma in Computer Science, UCD M.Sc., Ph.D. in Computer Science, UCD Professional Certificate in University Teaching & Learning, UCD Research Interests: Legal AI, digital forensics, machine learning, multi-agent systems, and information retrieval. Recent work includes NLP for regulatory analysis, crop yield prediction via neural networks, and AR-driven decision support systems. Grants & Projects: Principal Investigator: Transpire (AI Platform for Regulation) SFI Funded Investigator: CONSUS (Crop Optimization) PI: CeADAR Technology Centre Teaching roles include Deputy Programme Director for Software Engineering at Beijing-Dublin International College (BDIC) since 2014. Labs & Groups: UCD Forensics and Security Research Group, ML-Labs (SFI Centre for ML Training), and the Data Mining and Security Lab (BJUT).

Sheila Castilhoمشاهده پروفایل

استادیار

• Machine Translation
• Post-editing of Machine Translation
• Machine Translation Evaluation
• +۶ مورد دیگر

Dr. Sheila Castilho is an Assistant Professor at the School of Applied Language & Intercultural Studies, Dublin City University (DCU). She holds a PhD from DCU (2016) and a Master's from the University of Wolverhampton and University of Algarve. Her expertise lies in machine translation (MT), post-editing, and translation technology evaluation. She co-leads the New Trends in Translation Technology (NeTTT’22) conference and chairs DCU's Master in Translation Studies and Master in Translation Technology programs. Education: Licenciatura em Letras Inglês/Português (UNIOESTE University, Brazil) Master in Natural Language Processing (University of Wolverhampton & University of Algarve) PhD in Translation Technologies (Dublin City University) Research: Focuses on document-level MT evaluation, post-editing strategies, and user-centric MT assessment. Leads the DELA project and contributed to TraMOOC/iADAATPA initiatives. Published over 40 articles and co-edited 'Translation Quality Assessment: From Principles to Practice' (Springer, 2018). Grants & Projects: DCU PI for DELA (Document-level Evaluation) PRINCIPLE project (EU Low-resource MT) ELE (European Language Equality) initiative Labs/Teams: Active in ADAPT Centre (DCU) and collaborates with international NLP/MT communities (ACL, EMNLP, WMT).

• Edge Computing
• Cloud Computing
• Artificial Intelligence
• +۷ مورد دیگر

Hadi Tabatabaee is an Assistant Professor at the School of Computer Science, University College Dublin (UCD), leading the Sustainable Orchestration in Computing Continuum (SOC² Lab). His research focuses on sustainable orchestration of services across edge-cloud environments, emphasizing energy efficiency, carbon-aware systems, and AI-driven applications like large language models (LLMs). Key roles include Associate Editor for IEEE Access and Management Committee member of COST Action CA22151 (CYPHER). He holds a PhD in Computer Engineering from the University of Isfahan and has held academic positions at Maynooth University, Shahid Beheshti University, and Trinity College Dublin's CONNECT research program. Education: PhD (Computer Engineering, University of Isfahan), MSc (Computer Engineering), with a research visit at TU Delft (2010-2011). Certifications include Epigeum's Research Leadership and Research Integrity courses. Languages: Persian (fluent), Azerbaijani (spoken). Research Interests: Edge-cloud continuum, dynamic service placement, distributed AI workloads, LLM optimization, and sustainable resource management. Recent work includes zero-trust vehicular networks, parallel algorithms for recommender systems, and geospatial event processing. Awards: None explicitly listed, though his contributions include over 20 journal articles in IEEE/Elsevier/Springer venues. Professional Activities: IEEE Senior Member, TPC member for IEEE conferences, and reviewer for multiple journals. Teaching: Coordinates/teaches Cloud Computing, Computer Networks, and Principles of Computer Organization at UCD.

Venkata Virajit Garbhapuمشاهده پروفایل

پژوهشگر ارشد

• Optical Communications
• Network Optimization
• Artificial Intelligence in Networking
• +۴ مورد دیگر

Venkata Virajit Garbhapu (Viru) is a Research Fellow at the CONNECT Centre, Trinity College Dublin, specializing in optical networks with emphasis on physical layer optimization and cross-layer integration. Education: PhD, Institut Polytechnique de Paris (CIFRE scholar with Huawei) Laura Magistrale, Politecnico Di Milano His research focuses on maximizing network capabilities through physical layer impairment-aware frameworks, demonstrated by 52.8% training time reduction in distributed AI systems using 800G DCI links and superior failure recovery via optical circuit switching. Key contributions include per-channel power allocation algorithms balancing linear/nonlinear impairments and feasible C-band integration of classical/QKD signals through Raman noise-aware wavelength allocation. His work centers on developing sophisticated simulators enabling cross-layer optimization for functionalities like QKD and packet switching. Analysis of his 2019-2025 publications reveals a dominant trend toward AI-driven network automation, with increasing emphasis on digital twins and large language models for lifecycle management, alongside quantum-classical signal coexistence. The research consistently bridges theoretical algorithms with experimental demonstrations, showing progression from transfer learning for failure detection to advanced AI/quantum integration. No scientific awards were mentioned in available sources. His PhD was supported by a CIFRE industrial scholarship with Huawei, and he participated in the European QSNP project. No student advisement details are provided, though his BONSAI research addressed optical network failure management using transfer learning to overcome data scarcity. He operates within the CONNECT Centre ecosystem at Trinity College Dublin while maintaining active collaboration with Huawei Paris Research Center, reflecting strong industry-academia integration in optical communications research.

• 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.

Paul Clarkeمشاهده پروفایل

دانشیار

• Software Engineering
• Continuous Software Engineering
• Serverless Computing
• +۷ مورد دیگر

Paul Clarke is an Associate Professor in the School of Computing at Dublin City University (DCU), serving as Principal Investigator for the DTIF-funded Future Software Systems Architectures (FSSA) project focused on AI-driven software architectural transformation. He is a member of Lero (SFI Research Centre for Software) and represents Ireland on ISO/IEC JTC1 SC7 for software process standards, while providing industry advisory to Optimality Technologies Ltd and fourTheorem Ltd to bridge academia and practice. His research centers on continuous software engineering, serverless computing, and human aspects of development, with notable contributions to gamification in software engineering contexts and medical device software via the MDevSPICE® framework. He explores software process adaptive capability through empirical studies on occupational stress, virtual reality training environments, and blockchain applications for development integrity. Analysis of his 15 most recent publications (2023-2025) reveals three dominant trends: (1) AI/ML applications for software architecture modernization (microservices extraction, legacy system transformation), (2) gamification and virtual reality for developer training and process improvement, and (3) human factors investigations including occupational anxiety, sleep patterns, and avatar perception in metaverse environments. His work consistently employs multivocal literature reviews and empirical case studies across industrial contexts. Clarke leads the €2.1M FSSA project examining AI for monolith-to-microservices conversion and previously managed the MDevSPICE® medical device assessment framework. His industry advisory roles focus on commercializing research through Optimality Technologies (software analytics) and fourTheorem (cloud solutions), leveraging 15+ years of pre-academia experience at FINEOS, Arantech, and Logica Plc. He actively contributes to EuroSPI conference proceedings as both author and editorial board member.

Liting Zhouمشاهده پروفایل

استادیار

• Multimedia Retrieval
• Natural Language Processing
• Peer Learning
• +۳ مورد دیگر

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).

• Machine Learning
• Data Analytics
• Blockchain Technology
• +۷ مورد دیگر

Prof. Tahar Kechadi is a Principal Investigator at the Insight Centre for Data Analytics , specializing in Machine Learning & Statistics and Optimisation & Decision Analytics . His research spans interdisciplinary domains including agriculture, healthcare, and cybersecurity. University : Insight Centre for Data Analytics Role : Principal Investigator Ranks : Professor His current research focuses on applying machine learning to smart agriculture (e.g., crop yield prediction, data engineering), blockchain technologies (e.g., energy trading, e-voting), and privacy-preserving systems in healthcare and cybersecurity. Publications highlight advancements in multi-modal analysis , deep learning architectures , and game-theoretic clustering . Recent work explores data contamination in LLMs , privacy-aware blockchain systems , and distributed reputation management . His team develops tools for agro-climate modeling , medical diagnostics , and cloud forensic readiness . Contact: tahar.kechadi@insight-centre.org

Saeed Alsamhiمشاهده پروفایل

پژوهشگر ارشد

• Quality of Service (QoS)
• Space Technologies
• Multi-Robot Collaboration
• +۱۲ مورد دیگر

Saeed Alsamhi is a Senior Research Fellow at the Insight Centre for Data Analytics, University of Galway. His research spans cutting-edge domains including Quality of Service (QoS) , space technologies , multi-robot collaboration , and decentralized AI , with a focus on integrating UAVs, robotics, and digital twins into IoT and smart city frameworks. He has published over 211 papers, amassed 6,057+ citations, and maintains an H-index of 45. Key Research Areas: Edge Intelligence, Smart Environments, Industry 4.0/5.0, B5G, and multimodal healthcare solutions. Current Projects: ResNJRwater (Interreg), SmartPludi (Horizon Europe), and Irish Seafood Traceability (SFI). He serves as a Lead Guest Editor for journals like Drones and Energies , and as a technical committee member for IEEE conferences.

• Applied Artificial Intelligence
• Robotics
• Unmanned Aerial Vehicles (UAVs)
• +۵ مورد دیگر

Eleni Mangina is a Full Professor at the School of Computer Science, University College Dublin (UCD), and Vice Principal (International) for the College of Science. Her research focuses on applied artificial intelligence (AI), robotics, unmanned aerial vehicles (UAVs), and extended reality (XR) technologies with interdisciplinary applications in energy systems and education. She holds a PhD from the University of Strathclyde (UK), an MSc in Artificial Intelligence from the University of Edinburgh, and an MSc in Agricultural Science from the Agricultural University of Athens. Education : PhD, University of Strathclyde (UK), 2001 MSc in Artificial Intelligence, University of Edinburgh (UK) MSc in Agricultural Science, Agricultural University of Athens (Greece) HDip in University Teaching & Learning, UCD Research Interests : AI-driven optimization for energy and materials Xr applications in healthcare and education Citizen science and open data practices Robotics in early childhood education Smart city technologies Awards & Honors : 2022 CEN/CENELEC Standards Innovation Award 2021 Athena SWAN Bronze Award (School of Computer Science) 2020 UCD President's Teaching Award 2022 StandICT.eu Fellowship Grants & Projects : Coordinator of EU H2020 projects: ARETE, AHA, and FANTASIA Principal Investigator in SFI Energy Systems Integration Programme Lead on multiple XR and energy-related grants (2017-2025) Labs & Teams : Her lab develops XR solutions for education and energy, collaborating with EU and international partners. Current focuses include ethical XR standards and AI integration with metaverse platforms.

• Digital Forensics
• Cybersecurity
• Network Forensics
• +۵ مورد دیگر

Dr. Mark Scanlon is an Associate Professor in the School of Computer Science at University College Dublin (UCD), where he also serves as Founding Director of the UCD Forensics and Security Research Group and Programme Director of the MSc in Forensic Computing and Cybercrime Investigation. He holds a PhD in Remote Digital Forensic Evidence Acquisition and Analysis from UCD and is a Fulbright Scholar in Cybersecurity. His research focuses on digital forensics, cybersecurity, and IoT device analysis, with notable contributions in electromagnetic side-channel analysis, AI-driven forensic tools, and password cracking methodologies. Education: BA, University College Dublin MSc and PhD in Remote Digital Forensic Evidence Acquisition and Analysis, University College Dublin Professional Diploma in University Teaching & Learning, UCD Affiliations: Principal Investigator at CeADAR (National Centre for Applied AI) Senior Editor, Forensic Science International: Digital Investigation Scanlon’s research interests span digital forensics, cybersecurity, and AI applications in investigation. He has pioneered work in electromagnetic side-channel analysis for IoT devices, non-invasive cryptographic analysis, and leveraging LLMs for forensic efficiency. His work addresses challenges such as data deduplication, password cracking optimization, and improving practitioner workflows through automated tools like TraceGen and EMvidence frameworks. His articles highlight trends in AI integration (e.g., LLMs for evidence analysis), IoT forensic readiness, and practitioner challenges (via the DFPulse survey). Scanlon has secured grants including a Fulbright award for collaborative research and led initiatives in forensic education and ethical hacking training. His contributions bridge academic research and real-world forensic practices, emphasizing ethical considerations and tool development. Scientific Awards: Fulbright Scholar in Cybersecurity and Cybercrime Investigation In teaching, he coordinates modules such as Advanced Computer Forensics, Ethical Hacking, and OSINT Analysis, reflecting his commitment to advancing forensic education and cybersecurity training.

Professor Cathal Gurrin is the Head of the ADAPT Research Centre and a Full Professor in the School of Computing at Dublin City University. His research focuses on lifelog retrieval and video retrieval systems, with recent work on multimodal understanding and interactive retrieval interfaces. He has led the development of several retrieval systems showcased at the Video Browser Showdown and Lifelog Search Challenge. Recent publications demonstrate strong focus on multimodal datasets (CASTLE), EEG-based behavior analysis (DERCo), and next-generation video retrieval interfaces (VideoEase, VEAGLE).

• Biological and Artificial Vision
• Human Sensory Augmentation
• Secure Data Analytics
• +۳ مورد دیگر

Dr. Noel Murphy is an Associate Professor and Head of the School of Electronic Engineering at Dublin City University (DCU). He has held various leadership roles, including Associate Dean for Education in the Faculty of Engineering and Computing (2005-2007), Head of School (2007-2012, 2015-2018, and returning in 2021). He has been teaching at DCU since 1986 and has contributed extensively to academic governance, including roles on Academic Council and Governing Authority committees. Dr. Murphy holds a BA (Mod) in Theoretical Physics from Trinity College Dublin (TCD), a PhD from DCU (2003) on Information Theory models for Biological and Artificial Vision, and a part-time MA in Pure Mathematics from Maynooth University (2015). His research focuses on: Biological and Artificial Vision: Including Information Theoretic models and the work of Stephen Grossberg. Secure Data Analytics: Particularly leveraging SGX-enabled applications for data ownership control. Algebraic Number Theory: Exploring elliptic curves and Apéry's Constant. IoT and Edge Computing: Focusing on secure processing for IoT applications. Human Sensory Augmentation and Multimedia Information Retrieval. In addition to his teaching and leadership roles, Dr. Murphy has supervised numerous PhD and Master's students to completion. He has secured funding as Principal Investigator or co-Investigator on national and EU-funded research projects. He is affiliated with DCU's Entwine Research Centre. Outside academia, Dr. Murphy is Honorary Secretary of the Irish Light Aviation Society, holds a Private Pilot’s License, and is involved in aircraft restoration projects, including a 1940 Piper J5 and a Vans RV-8.

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