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.

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.

James Sweeneyمشاهده پروفایل

استاد

• Machine Learning
• Time Series Analysis
• Geospatial Statistics
• +۳ مورد دیگر

James Sweeney serves as Professor in the Department of Mathematics and Statistics at the University of Limerick, concurrently holding memberships in the Centre for Battery and Energy Materials Research and the Mathematics Applications Consortium for Science and Industry (MACSI). Actively accepting PhD students, his research bridges theoretical mathematics with practical industry applications across diverse sectors including energy materials, real estate, and public health. His research portfolio demonstrates exceptional interdisciplinary range, with core expertise in machine learning algorithms (particularly time series classification and neural networks), geospatial statistics for property valuation, and epidemiological modeling for disease surveillance. Key methodological contributions include evolutionary algorithms for optimization, dissimilarity-preserving representation learning, and flexible geospatial smoothing techniques that address complex real-world data challenges. Analysis of his 23 publications (2015-2024) reveals accelerating scholarly output since 2020, with 2024 being particularly prolific. His work consistently targets high-impact applications: developing diagnostic thresholds for bovine tuberculosis, modeling COVID-19 transmission dynamics in Dublin, and creating neural network solutions for geodemographic clustering. This trajectory reflects deepening engagement with computational approaches to solve pressing societal problems through mathematical innovation. As a PhD supervisor, he cultivates next-generation researchers in advanced computational methods. His collaborative framework extends through MACSI's industry partnerships and the Centre for Battery and Energy Materials Research, where mathematical modeling directly informs energy technology development. These dual affiliations position him at the critical intersection of academic research and industrial application, particularly in Ireland's growing tech and energy sectors. His laboratory activities center around computational mathematics teams within MACSI, focusing on applying statistical learning to battery materials research and real-world data challenges. Current projects involve time series analysis for sensor data, geospatial modeling for economic forecasting, and optimization algorithms for veterinary epidemiology – demonstrating remarkable methodological versatility across traditionally disparate domains.

• Natural Computing
• Financial Modelling
• Operations Research
• +۳ مورد دیگر

Professor Anthony Brabazon is the College Principal and Dean of the UCD College of Business at University College Dublin. He holds a prominent administrative role alongside his academic contributions in natural computing and business analytics. His research focuses on natural computing theory, financial modeling using evolutionary algorithms, and complex adaptive systems in business contexts. Brabazon co-founded the Natural Computing Research and Applications Group (NCRA) at UCD, which explores theoretical and practical applications of bio-inspired algorithms. Education: B Comm and Dip. Prof Accounting – University College Dublin DBA – Kingston University, London DPA and Dip Stat – University College Dublin and Trinity College Dublin MBA – Heriot-Watt University, Edinburgh MS – Stanford University Research Interests: Anthony's work bridges computational intelligence and finance, with contributions to genetic programming, foraging-inspired optimization, and business analytics. His research highlights the application of evolutionary algorithms to real-world problems in finance, operations research, and organizational strategy. Grants and Collaborations: HEA Support for COVID-19 Related Research (2020–2025) Financial Mathematics and Computation Cluster (FMC²) (2009–2016) Teaching: Coordinated MAcc Management Accounting courses at the postgraduate level (2018–2019). Professional Activities: Member of CIMA Ethics Board Editorial board roles in multiple journals Founder of EvoBAFin workshop on computational finance

• Bioinformatics
• Protein Structure Prediction
• Machine Learning
• +۳ مورد دیگر

Gianluca Pollastri is an Associate Professor in the School of Computer Science at University College Dublin (UCD). He leads a research group focused on machine learning applications in bioinformatics, particularly protein structure prediction and analysis. His academic roles include Associate Professor since 2016, Senior Lecturer from 2008, and Lecturer from 2003. He earned an MSc from the University of Florence and a PhD from the University of California, Irvine. His research integrates deep learning and neural networks to address challenges in protein subcellular localization, secondary structure prediction, and intrinsically disordered regions. Key tools developed include SCLpred, PaleAle, Porter, and PUNCH2. He has secured grants from Science Foundation Ireland, the Health Research Board, and UCD. Pollastri’s work emphasizes rigorous validation of machine learning methods in biology, as outlined in the DOME framework. His lab has produced over 100 peer-reviewed articles, with recent focus on leveraging pre-trained language models (PLMs) for protein analysis. Education: MSc, University of Florence PhD, University of California, Irvine Awards: Best M.Sc. Thesis in Artificial Intelligence (1999) Best Student Project in Artificial Intelligence (1997) His teaching includes modules on Bioinformatics, Connectionist Computing, and Programming. He coordinates research collaborations and maintains a lab with postdoctoral fellows and graduate students.

Malachy Eatonمشاهده پروفایل

دانشیار

• Genetic Algorithms
• Humanoid Robotics
• Artificial Intelligence
• +۵ مورد دیگر

Malachy Eaton is an Associate Professor in the Department of Computer Science and Information Systems at the University of Limerick. His research focuses on evolutionary computation, humanoid robotics, and graph theory. Institution: University of Limerick Department: Computer Science and Information Systems Academic Rank: Associate Professor Email: Malachy.Eaton@ul.ie His work spans Genetic Algorithms , Humanoid Robotics , and Artificial Intelligence , with notable contributions to evolutionary robotics, graph layout optimization, and computational intelligence. Research includes: Evolutionary approaches to humanoid robot motion Simulated annealing for graph drawing Force-directed layout algorithms Bridging simulation-to-reality gaps Edge crossing reduction techniques Data mining to evolutionary robotics Key themes in his publications reflect strong expertise in Genetic Algorithms (100% usage), Humanoid Robots (66-100%), and Artificial Intelligence (100%).

• Hardware Design
• VLSI Systems
• Digital Circuit Optimization
• +۴ مورد دیگر

Rajkumar Sarma is a Research Fellow at the Department of Computer Science & Information Systems at Lero – the Research Ireland Centre for Software, University of Limerick. His work focuses on hardware design, VLSI systems, and optimization techniques for digital circuits. He specializes in areas such as low-power architectures, floating-point arithmetic, and evolutionary algorithms for automated design. His research emphasizes hardware-software co-design, reliability analysis under PVT (Process, Voltage, Temperature) variations, and efficient implementations of multiply-accumulate (MAC) units critical to digital signal processing and image processing applications. Key technical contributions include the development of the UCM algorithm for delay optimization, grammatical evolution for synthesizable HDL code generation, and novel approaches to reduce power consumption in MAC architectures. His work bridges theoretical algorithmic innovation with practical VLSI implementation challenges, addressing both performance and reliability under extreme operating conditions. Rajkumar’s publications span 2012–2025, with a strong focus on digital circuit design, including hybrid adders, low-power flip-flop implementations, and quantum gate-based reversible circuits. His research also extends to reliability analysis of electronic components like multi-layer ceramic capacitors. He has utilized advanced simulation tools such as Cadence ADE-XL for accelerated PVT analysis, demonstrating expertise in both computational modeling and hardware validation. While no specific awards or grants are listed, his extensive publication record reflects sustained engagement with cutting-edge challenges in computer architecture and VLSI systems design.

• Signal Processing
• Machine Learning
• Computer Engineering
• +۳ مورد دیگر

Ehsan Namjoo serves as a Research Fellow in the Department of Electronics & Computer Engineering at the University of Limerick, with a primary affiliation at Lero – the Irish Software Research Centre. His multidisciplinary work bridges theoretical signal processing, machine learning applications, and hardware implementation for real-world systems. His research spans signal processing (DOA estimation under non-ideal noise conditions, EEG source imaging), machine learning (explainable AI for medical diagnostics, feature selection in cancer detection), and computer engineering (polar code decoders, visible light communication systems). Notable biomedical applications include breast cancer diagnosis and epileptic source analysis, while cybersecurity work focuses on intrusion detection in cloud environments. Recent publications (2021-2025) reveal a consistent trajectory toward developing lightweight, interpretable models for tabular medical data alongside robust signal processing frameworks for communication systems. His work increasingly integrates hardware-aware algorithms, particularly in polar coding implementations, and emphasizes practical validation through experimental demonstrations in visible light networks. As an active Lero researcher, Namjoo participates in Ireland's national software research ecosystem, contributing to interdisciplinary projects that connect theoretical innovations with healthcare, communications, and security applications through collaborative frameworks.

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.

Elizabeth Shottonمشاهده پروفایل

استاد

• Sustainable Architecture
• Maritime Heritage
• Timber Construction
• +۶ مورد دیگر

Professor Elizabeth Shotton is affiliated with University College Dublin (UCD) in the School of Architecture, Planning and Environmental Policy . Her academic career spans teaching, research, and leadership roles, including Vice Principal for Equality, Diversity & Inclusion (2017–2020) and Interim Head of Landscape Architecture (2023). Teaching: Focuses on Construction Technology , Design Studio , and Sustainable Building Practices . Research: Centers on Maritime Heritage , Timber Reuse , and Design for Disassembly , with projects like the Modular Adaptable SHelter (MASH) and Minor Harbours of Ireland . Grants: Leads projects funded by the Irish Research Council , ESRC/IRC Network Grant (Harbourview), and Fulbright TechImpact Scholar . Awards: Recipient of the University Award for Outstanding Contribution to Student Learning (2021). Academic Leadership: Chaired UCD's Athena Swan Bronze Award application (2019) and served on the NCAD Programme Board and Appeals Committee . Research Trends: Her work bridges historical maritime engineering with sustainable design , emphasizing community-driven documentation and innovative timber construction. Key collaborations include Cardiff University (Harbourview) and international partners in the InFutUReWood project. Her Design for Disassembly research has influenced military shelter design via the MASH SFI Challenge project. Scientific Awards: University Award for Outstanding Contribution to Student Learning (2021) Advising & Grants: Supervised PhD students (e.g., Cian O'Loinsigh ) and secured major grants such as Harbourview (2021–2022), InFutUReWood (2019–2022), and Visualising Vernacular Harbours (2017–2018). Labs & Teams: Collaborated with UCD's School of Civil Engineering and international institutions in projects like WoodWeldiT and Tectonic Culture .

• Data Communications
• Network Security
• Software-Defined Networking (SDN)
• +۴ مورد دیگر

Dr. Martin Collier is an Associate Professor in the School of Electronic Engineering at Dublin City University and director of the Entwine Centre, focusing on IoT infrastructure. His research spans data and computer communications, network security, energy-efficient networking, and SDN/NFV. He leads projects like Horizon 2020's INPUT and FP7's ECONET, collaborating with IBM on data centre network design. His work emphasizes switch fabrics, green routers, and optical technologies. Research Interests: Switching/Routing, SDN, NFV, IoT, Energy Efficiency, Data Centre Networks. Recent Projects: INPUT (SDN/NFV personal cloud services), ECONET (energy efficiency), and IBM-funded data centre design. Laboratory activities include NetFPGA-based testing and SDN implementations. Teaching: Modules include Broadband Networks (EE552), Network Programming (EE562), and Communications Theory (EE450). Supervises final-year and MEng projects. Labs/Teams: Switching & Systems Lab (NetFPGA testbed), Entwine Centre (IoT infrastructure).

• Constraint Programming
• Boolean Satisfiability
• Artificial Intelligence
• +۵ مورد دیگر

Steve Prestwich is a Lecturer at the School of Computer Science and Information Technology, University College Cork. He specializes in Artificial Intelligence, Data Analytics, and Algorithmics, with research interests spanning constraint programming, Boolean satisfiability, and hybrid search methods. Education: BA (Hons) Mathematics from University of Oxford, MSc and PhD in Computer Science from University of Manchester. Research Focus: His work integrates constraint programming, SAT solving, and metaheuristics for optimization under uncertainty, with applications in inventory control, protein design, and stochastic modeling. Awards: Runner-up, Constraint Modelling Challenge Bronze medal, SAT'05 Solver Competition

Diarmuid O'Donoghueمشاهده پروفایل

استادیار

• Computational Creativity
• Analogical Reasoning
• Natural Language Processing
• +۴ مورد دیگر

Diarmuid O'Donoghue is an Assistant Professor in the Faculty of Science & Engineering at Maynooth University, specializing in Computational Creativity and Analogical Reasoning . His research explores topological similarities between text and source code to develop cognitively inspired systems for problem-solving and bias detection. Co-PI of the Modelling implicit bias project (€21/FFP-P/10118) Senior Scientific Coordinator for the €2.6M EU-funded Dr Inventor project Key research areas include: Latent homomorphism detection in lexical data Comparative analysis of LLMs and analogical systems Formal specification generation from code/text His work has shaped undergraduate project frameworks with ethical GenAI integration . Publications span ICCC , GECCO , and journals like Artificial Intelligence Review .

Anh Vu Voمشاهده پروفایل

استادیار

• LiDAR
• Urban Science
• Spatial Data Management
• +۴ مورد دیگر

Dr. Anh Vu Vo is an Assistant Professor at University College Dublin's School of Computer Science, specializing in high-scalability algorithms for LiDAR and urban spatial datasets. He holds a PhD from UCD, a Master's from the University of Melbourne, and a Bachelor's from HCMC University of Architecture. Roles : Lecturer/Assistant Professor since 2024, Postdoctoral Research Fellow (2019–2022), Research Scientist at NYU (2018–2019). Research Interests : LiDAR, Urban Science, Spatial Data Management, Distributed Computing, and Big Data. Key projects include CAMEO (Earth Observation platform), UrbanARK (flood risk assessment), and AIMVIE (mangrove mapping). He has authored over 30 peer-reviewed publications and secured grants such as the SFI Future Innovator Prize. Awards : 2022 EODisrupt Winner, 2015 IEEE GRSS Data Fusion Contest First Prize, Australian Endeavour Award. Teaching : Spatial Information Systems, Urban Sensing, and graduate-level courses. His work focuses on integrating LiDAR data with advanced computing frameworks to address urban challenges like flood risk and infrastructure planning.

• 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 .