جستجوی استاد راهنمای دانشگاهی

Conor Ryanمشاهده پروفایل

استاد

• Genetic Programming
• Genetic Algorithms
• Grammatical Evolution
• +۷ مورد دیگر

Conor Ryan is a Professor in the Department of Computer Science & Information Systems at the University of Limerick. He is a Science Foundation Ireland-funded Investigator since 2002 and a member of multiple research centres including Lero – the Irish Software Research Centre and the Limerick Digital Cancer Research Centre. His research focuses on Genetic Programming, Grammatical Evolution, and their applications in domains like healthcare analytics, digital circuit design, and financial modeling. He has authored over 250 publications, with recent work emphasizing automated feature selection in medical diagnostics, neural architecture search, and blockchain ecosystems. Teaching includes courses on Foundations of Computer Science and Computer Games Programming. Research interests span evolutionary computation, machine learning, and interdisciplinary applications. Collaborations involve global institutions, reflecting his work's impact across computer science, engineering, and healthcare. His research has addressed challenges in breast cancer diagnosis via genetic algorithms, cryptocurrency volatility prediction using random forests, and automated generation of digital circuits. Ongoing projects explore interpretability in AI, energy-efficient computing, and sustainable transport systems through predictive analytics. Professional memberships include roles in the Centre for Research Training in Foundations of Data Science and the Data-Driven Computer Engineering Research Centre, underscoring his commitment to interdisciplinary innovation.

• 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.

• 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.

• Digital Signal Processing
• Communication Systems
• Biomedical Signal Processing
• +۶ مورد دیگر

Dr. Barry Cardiff is an Assistant Professor in the School of Electrical and Electronic Engineering at University College Dublin (UCD), where he has been a member of academic staff since September 2013. His career spans both industry and academia, with significant experience at Nokia Mobile Phone (UK) Ltd and Silicon & Software Systems (S3 group) before returning to complete his PhD at UCD. Education: B.Eng (1992), M.Eng.Sc. (1995), PhD (2011) from University College Dublin Professional Experience: Design Engineer at Nokia (1993-2001), Systems Architect at S3 group (2001-2007, 2011-2013) Current Position: Assistant Professor at UCD School of Electrical and Electronic Engineering Dr. Cardiff's research focuses on Digital Signal Processing applications in communication systems, with particular emphasis on theoretical analysis and practical implementation. His work bridges traditional communication theory with emerging biomedical applications, especially in wearable IoT sensors. He has made significant contributions to power/complexity reduction techniques in circuit design, specifically DSP algorithms for digitally assisted analog circuits. His research program addresses critical challenges in biomedical signal processing, sensor fusion, and efficient data transmission for healthcare applications. His recent publications demonstrate a strong trend toward biomedical applications of signal processing techniques, with a focus on ECG analysis, atrial fibrillation detection, and respiratory rate estimation using multimodal sensor fusion. The research shows a clear progression from traditional communication systems toward healthcare applications, with an emphasis on edge computing solutions that reduce power consumption in wearable devices. IEEE BioCas best paper award (2024) IEEE senior member since 2019 Active reviewer for multiple IEEE journals including Transactions on Biomedical Circuits and Systems, Circuits and Systems, and VLSI Systems Dr. Cardiff has supervised numerous research projects and has been instrumental in developing curriculum for digital communications, signal processing, and wireless systems. His teaching philosophy emphasizes open, friendly, and hands-on approaches that encourage independent thinking. He coordinates multiple modules including Communication Theory, Digital Electronics, DSP Technology, and Wireless Systems, demonstrating his commitment to both theoretical foundations and practical applications of electrical engineering principles. His research group works at the intersection of signal processing, machine learning, and biomedical engineering, developing innovative solutions for wearable healthcare monitoring. Current projects focus on event-driven processing architectures, decentralized classification systems, and signal quality-aware fusion techniques that enable robust performance in noisy real-world environments.

• Software Engineering
• Search-Based Software Engineering
• Automated Refactoring
• +۴ مورد دیگر

Dr. Mel Ó Cinnéide is an Associate Professor at the School of Computer Science, University College Dublin. He holds a PhD from Trinity College Dublin (2001) and has over three decades of experience in academia and industry. His research focuses on automated refactoring, search-based software engineering, design patterns, and energy-efficient software development. He leads the Masters in Advanced Software Engineering program at UCD and has received multiple research grants and best paper awards. Prior to academia, he worked as a software engineer at Philips (Netherlands) and Motorola (Cork). Education: BSc in Computer Science, University College Cork MSc in Computer Science, University College Cork PhD in Computer Science, Trinity College Dublin Diploma in Gaeilge Fheidhmeach (Computing Irish), UCD Research interests emphasize practical applications of refactoring techniques to improve software quality and energy efficiency. He pioneers tools like Code-Imp and RefDetect for automated refactoring, integrating multi-objective optimization and interactive systems. His work bridges theoretical software engineering principles with real-world industry challenges. Awards and Grants: - Best Paper Awards in peer-reviewed conferences - Competitive research grants supporting software engineering projects Advising & Leadership: - Director of UCD's Masters in Advanced Software Engineering - Supervisor of numerous academic and industrial projects Labs & Projects: - Co-lead of the CodeImp Project (automated search-based refactoring) - Involved in international workshops on refactoring and software engineering

• Software Engineering
• Smart Cities
• Internet of Things
• +۴ مورد دیگر

Siobhán Clarke is a Professor at the School of Computer Science and Statistics, Trinity College Dublin, specializing in software systems for smart urban environments . Her work addresses dynamic software adaptation in large-scale, mobile IoT ecosystems , with a focus on QoS optimization and collaborative agent models . Director, Enable : National SFI IoT Research Programme Director, Future Cities Centre for Smart & Sustainable Cities Co-Lead, ADVANCE : SFI Centre for Advanced Networks Co-PI, CONNECT (Future Networks) and Lero (Software Research) Her research spans smart city infrastructure , edge computing , and multi-agent coordination , informed by 15+ years of publications on service-oriented architectures , QoS prediction , and self-adaptive systems . Key project contributions include DIVERSIFY (2016) and TRANSFoRm (2015). Scientific awards include election to the Royal Irish Academy (2023) and a Best Student Paper at IEEE ICWS 2011. She has supervised 20+ PhD/MSc students, including Fan Li (2020: SLA Negotiation Systems), Gary White (2020: IoT QoS Forecasting), and Andrei Palade (2019: Stigmergic Optimization).

Brian Ó Raghallaighمشاهده پروفایل

استادیار

• Digital Terminology
• Onomastics
• Folkloristics
• +۶ مورد دیگر

Dr. Brian Ó Raghallaigh is an Assistant Professor in Fiontar & Scoil na Gaeilge at Dublin City University (DCU). He holds a BA (Mod.) in computational linguistics and a PhD in speech technology from Trinity College Dublin. His research focuses on digital terminology, onomastics, folkloristics, phonetics, and language technology. He is Co-Principal Investigator of the AHRC-IRC 'Decoding Hidden Heritages' project (2021–2024) and Principal Investigator of the Department of the Gaeltacht-funded 'Logainm Placenames Database of Ireland' project. Education: BA (Mod.) in Computational Linguistics (Trinity College Dublin), PhD in Speech Technology (Trinity College Dublin) Roles: Technology Manager of the Gaois research group, Module Coordinator for Irish Linguistics (LIG1004), Co-coordinator for Corpus Research (LIG1010) Publications: Authored Fuaimeanna na Gaeilge , creator of fuaimeanna.ie , and co-editor of Decoding the Oral Traditions of Scotland and Ireland . His research interests span terminology, placename studies, digital humanities, and language preservation. He leads projects like Terminologue (a cloud-based terminology platform) and collaborates on initiatives such as the EU-GA terminology project. He is active in professional organizations like SNSBI, SIEF, and CIGILT. Grants & Projects: Funded by AHRC/IRC, Department of the Gaeltacht, RIA. Key projects include Logainm.ie , Gaois surname database , and Historical Dictionary of Modern Irish . Labs/Teams: Gaois research group (focused on language technology), Terminologue (terminology management), and collaborations with the Digital Repository of Ireland (DRI).

James Pattenمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Software Engineering
• Source Code Analysis
• +۳ مورد دیگر

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.

• Energy Efficient Networking
• Hardware Acceleration
• Cryptography Algorithms
• +۴ مورد دیگر

Dr. Xiaojun Wang is an Associate Professor at the School of Electronic Engineering, Dublin City University (DCU). He holds a BEng and MEng from Beijing University of Posts and Telecommunications (BUPT) and a PhD from Staffordshire University (UK). His research focuses on energy-efficient networking, hardware acceleration for packet classification/deep inspection, and cryptography algorithms. He has been instrumental in establishing China-Ireland academic collaborations, including the China-Ireland International Conference on Information and Communications Technologies (CIICT), and coordinated a successful joint Telecommunications Engineering program with Wuhan University (2006–2012). He is also a member of DCU's Entwine Research Centre. Key roles include Head of China Affairs at DCU (2002–2007), contributing to institutional partnerships. His technical work spans green energy solutions for networks, quantum computing protocols, and hardware-software co-design for cryptographic systems. He has led projects on edge computing security, vehicular communication optimization, and blockchain-based trust frameworks. Educations: BEng in Computer & Communications, BUPT (1984) MEng in Computer Applications, BUPT (1987) PhD in Engineering, Staffordshire University (1992) Affiliations: Member of Entwine Research Centre Former Head of China Affairs, DCU His recent publications emphasize secure edge computing, quantum steganography, and 5G resource orchestration. He has pioneered energy-efficient router architectures and contributed to standards for vehicular networks and blockchain trust systems.

• Genetic Programming
• Symbolic Regression
• Feature Selection
• +۳ مورد دیگر

Dr. Muhammad Sarmad Ali is a Researcher at Lero - The Irish Software Research Centre , affiliated with the Department of Computer Science & Information Systems . His work focuses on Genetic Programming and Symbolic Regression with a particular emphasis on grammar-based optimization techniques. Institution: Lero - The Irish Software Research Centre Department: Computer Science & Information Systems Academic Role: Researcher Research Interests: Genetic Programming (69%), Symbolic Regression (100%), Feature Selection (100%), Fuzzy Pattern Trees (100%), Program Size Reduction (55%), and Production Rules (100%). Recent Publications (2009-2023): 8 research outputs including SN Computer Science journal articles and GECCO/ICAART conference contributions. Key trends show a focus on grammar-based AI , evolutionary algorithms , and automated feature engineering .

Abdul Razzaqمشاهده پروفایل

استادیار

• AI-driven Software Engineering
• Developer Experience
• Software Metrics and Evaluation
• +۷ مورد دیگر

Dr. Abdul Razzaq is an Assistant Professor in the Department of Computer Science & Information Systems at the University of Limerick, affiliated with Lero – the Irish Software Research Centre. His research focuses on AI-driven software engineering, developer experience, empirical software analytics, and cloud computing, aiming to enhance developer productivity and bridge academic-industry gaps. He holds a PhD in Software Engineering from Lero, with prior degrees in Computer Science. His work has yielded 432 citations and led to industry-adopted tools like JITTAC licensed by Huawei. Education: PhD (2019, Lero), MSc & BSc in Computer Science. Research interests include AI applications in code parsing/refactoring, developer context modeling, and tool standardization. He actively supervises PhD/MSc students in AI, NLP, and software engineering, emphasizing research scaffolding and guided autonomy. Publications appear in ACM TOSEM, IEEE TSE, and EMSE. Industry collaborations include Huawei, ACI Worldwide, and GLOCC Group. He contributes to education through UDL principles in curriculum design and led QQI revalidation for Data Analytics programs. Engagements include COVIGILANT project and AI policy discussions. Member of ACM & IEEE, with reviewing roles at IEEE TSE and Wiley JSEP.

• Evolutionary Algorithms
• Genetic Programming
• Semantic-Based Genetic Programming
• +۷ مورد دیگر

Dr. Edgar Galván is an Associate Professor in the Department of Computer Science at Maynooth University, Faculty of Science & Engineering. He holds a PhD in Computer Science from the University of Essex and has held senior research roles at institutions like University College Dublin and Trinity College Dublin. His research focuses on Evolutionary Algorithms, Genetic Programming, and their applications in optimization, games, and circular economy challenges. Education : PhD in Computer Science, University of Essex MSc (Hons) in Artificial Intelligence (Research), University of Veracruz BSc (Hons) in Computer Science, University of Veracruz Research Interests : Dr. Galván pioneers work in semantic-based Genetic Programming, neutrality and locality in evolutionary algorithms, and applications in combinatorial optimization and energy systems. He also explores AI-driven solutions for the circular economy, including material reuse and policy design. Grants & Projects : REBUILD (€449,879): Reimagining buildings as material banks for the circular economy (2024–2027) VISION (€149,874): Circular business models to reduce virgin material use in construction (2023–2026) Stochastic Bio-inspired Evolutionary Algorithms (€267,000): Dynamic optimization problems (2014–2017) Awards : Top 1% of researchers in Genetic Programming (UCL, 2020) Elected member of Mexico’s National Research System (2015) Marie Curie Fellowship (Irish Research Council, 2014) Professional Activities : Chair of ACM Genetic and Evolutionary Computation Conference committees, Programme Committee member for IEEE Congress on Evolutionary Computation, and Scientific Adviser for research councils in Ireland, France, and Mexico.

• Quantum Computing
• Machine Learning
• Fairness in Machine Learning
• +۳ مورد دیگر

Simon Caton is an Assistant Professor of Computer Science at University College Dublin (UCD) and a founding member of the UCD Centre for Quantum Engineering, Science, and Technology (C-QuEST). He holds a BSc and PhD from Cardiff University and a Professional Diploma in University Teaching and Learning from UCD. His academic roles include Programme Director for the MSc Computer Science (Conversion) and Deputy Head of Teaching and Learning at UCD's School of Computer Science. Research Interests: Quantum computing applications (quantum machine learning, reinforcement learning control), fairness in machine learning, social media analysis, and distributed systems. Current projects focus on quantum control landscapes, customer needs prediction, and inclusive policy analysis for migrants in Ireland. Grants: Lead investigator on the Science Foundation Ireland-funded ML-Labs project (2019–2027), focusing on accelerating Ireland's machine learning expertise. Teaching: Coordinates modules like Quantum Machine Learning, Java Programming, and Team Software Project. Active in curriculum development for conversion courses and work placement programs. Professional Service: External Examiner for TU Dublin and TU Shannon. Previously held academic positions at National College of Ireland and Karlsruhe Institute of Technology (KIT).

John J Collinsمشاهده پروفایل

دانشیار

• Compiler Optimization
• Software Parallelization
• Robotics
• +۴ مورد دیگر

John J Collins is an Associate Professor at the University of Limerick, affiliated with the Department of Computer Science & Information Systems and Lero – the Research Ireland Centre for Software. His research focuses on compiler optimization, software parallelization, robotics, and evolutionary algorithms. Notable contributions include work on grammatical evolution and empirical studies in software requirements engineering. He has authored 36 research outputs since 1997, including a comprehensive handbook on grammatical evolution. Research Interests: Compiler flag optimization using genetic engineering Robotics (mobile robot control, SLAM) Machine vision applications Parallelization techniques in multi-core architectures Grammatical evolution methodologies Key Publications: His recent work includes a 2019 study on requirement engineering challenges across 11 organizations and a 2017 case study on data decomposition for parallel software systems. The 2018 Handbook of Grammatical Evolution remains a foundational text in evolutionary computing. Advising & Grants: While no specific advisees are listed, his research has been supported through institutional affiliations with Lero and the Department of Computer Science. Active in both academic publishing and applied software research. Labs/Teams: Principal member of Lero – the Irish Software Research Centre, contributing to collaborative projects in software systems and AI-driven development.

• Genetic Programming
• Evolutionary Algorithms
• Combinatorial Optimisation
• +۶ مورد دیگر

Dr. Edgar Galván is an Associate Professor in the Department of Computer Science at Maynooth University's Faculty of Science & Engineering. He is a leading expert in Genetic Programming (GP) and Evolutionary Algorithms, with a focus on semantic-based approaches, neutrality, and multi-objective optimization. His work spans applications in combinatorial optimization, gaming (e.g., Carcassonne), and software engineering, including neuroevolution for deep learning architectures. Current Affiliation: Maynooth University Previous Roles: Senior Researcher at University College Dublin, Trinity College Dublin, and INRIA Paris-Saclay Research interests include: Semantic-based Genetic Programming Multi-objective Evolutionary Algorithms Monte Carlo Tree Search Circular Economy Applications Privacy-Preserving Optimization Neuroevolution in Autonomous Systems His recent publications analyze semantic diversity in GP, neural architecture search, and privacy-aware swarm optimization. Key awards include being ranked among the top 1% of GP researchers by University College London (2020), a Marie Curie Fellowship (2014), and a Best Paper Award at ECTA 2015. Current Projects: REBUILD (Circular Economy Buildings, 2024-2027), VISION (Circular Business Models, 2023-2026) Previous Grants: Stochastic Bio-inspired Algorithms (2014-2017, €267k), circAI (2022-2023, €142k) Dr. Galván serves on program committees for IEEE, ACM, and Springer conferences, and as Scientific Adviser for institutions in Ireland, France, and Mexico. His work bridges theoretical GP analysis with real-world applications in energy optimization and AI.