جستجوی استاد راهنمای دانشگاهی

Brendan McCarthy is an Assistant Professor in the Department of Accounting & Finance at the University of Limerick's Kemmy Business School. His work bridges practical experience with academic research, focusing on employee voice in tax and professional services, AI's impact on taxation, and pedagogical innovation in higher education. Education: Ph.D. in Taxation (University of Limerick), MSc in Taxation (University of Limerick), BA in Law and Accounting (University of Limerick) McCarthy's research explores employee voice mechanisms in Big 4 accounting firms, the rhetoric versus reality of professional practice, and AI's transformative potential in tax careers. His pedagogical work addresses co-creation of content and its impact on academic achievement. His recent publications highlight trends in AI integration, employee engagement in professional firms, and educational co-creation. These works span subfields like tax compliance, AI ethics, learning analytics, and workplace communication. McCarthy contributes to university governance as UL Kemmy Business School representative to the UL Student Retention Working Group and UL representative to the Irish Accounting and Finance council. He actively supervises student research projects and incorporates his decade of tax practice into teaching.

• Taxation
• Accounting
• Employee Voice
• +۴ مورد دیگر

Finbarr Murphy is an Associate Professor in Quantitative Finance and Emerging Risk at the University of Limerick , where he is also the Executive Dean . He is affiliated with the Centre for Emerging Risk Studies , Lero – the Irish Software Research Centre , and the Centre for Research Training in Foundations of Data Science . Education: Bachelor of Engineering (1992) Master of Arts (2004) Research Interests focus on quantitative finance , emerging technological risk , and their intersections with machine learning , cybersecurity , and transportation safety . His work spans EU-funded H2020 and Horizon Europe projects, as well as Science Foundation Ireland (SFI) initiatives. Recent Publications highlight predictive modeling for insurance premiums, cyber risk prediction frameworks, trust in generative AI applications, electric vehicle risk comparisons, and European cyber insurance market efficacy. These align with his expertise in data-driven risk analysis and financial technology . Scientific Awards include Fulbright Scholar (2012) Postgraduate Course of the Year - Business (Winner, 2011; Shortlisted, 2012, 2014) Erasmus Mundus Action 2 Scholarship (2014) Professional Roles include advisory positions for industry and the EU Commission, alongside prior experience as a Fixed Income Quantitative Product Specialist (UBS Warburg), CEO (Alatto Technologies Ltd), and senior trading/IT roles at Merrill Lynch and Credit Suisse First Boston.

• Quantitative Finance
• Emerging Technological Risk
• Machine Learning
• +۳ مورد دیگر

Dr. Deniz Mevlevioğlu serves as a Lecturer in the School of Computer Science and Information Technology at University College Cork, Ireland, based in Office 1.81 of the Western Gateway Building. His contact details include email Deniz.Mevlevioglu@ucc.ie and phone +353 21 420 5929, with ORCID identifier 0000-0003-2776-1304. His research centers on virtual reality applications for mental health, specifically: Real-time anxiety detection using biosensors and convolutional neural networks during VR therapy Development of immersive cognitive assessments like the Emotional Virtual Reality Stroop Task Integration of physiological feedback mechanisms (e.g., visual respiratory monitoring) in exposure therapy Analysis of his publication history reveals a consistent focus on adaptive VR therapeutic systems. His work bridges computer science and clinical psychology through real-time biosignal analysis, with publications spanning technical implementations (2021-2024), systematic reviews, and pilot clinical studies. Key innovations include convolutional neural network-based anxiety classifiers and respiratory biofeedback integration, all targeting enhanced efficacy of VR-based mental health interventions through physiological computing.

• Virtual Reality
• Affective Computing
• Biosignal Processing
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Rafael de Andrade Moral is a Professor of Statistics at Maynooth University's Faculty of Science & Engineering (since 2025), with prior roles as Associate Professor (2023-2025) and Assistant Professor (2018-2023). He holds a PhD in Statistics (University of São Paulo, 2014-2017) and dual bachelor's degrees in Biology and Education. His work bridges Statistical Ecology , Computational Biology , and Data Science , focusing on modeling ecological systems, agricultural pest dynamics, and biodiversity-ecosystem function relationships. Key research themes include Bayesian modeling , multivariate ecological forecasting , and machine learning applications . He founded the Theoretical and Statistical Ecology Research Group and serves on committees like the Young-ISA Chair . His recent articles span topics like insect abundance forecasting , weed-crop competition under climate change , and neuroinformatics-based learning analysis , reflecting interdisciplinary engagement. Scientific accolades include the Young Statistician Showcase Prize (2018), A-mu-sing Competition First Place (2021), and Maths Week Award (2022). He has advised three PhD students and contributed to over 50 peer-reviewed publications. Active in teaching innovation (e.g., Teaching Statistics through Music ), he also provides statistical consultancy to organizations like NIBIO and Jomakol .

• Statistical Modelling
• Ecology
• Wildlife Management
• +۳ مورد دیگر

Professor Gerard (Gerry) Lacey is Professor of Electronic Engineering at Maynooth University within the Faculty of Science and Engineering. He also serves as Head of the Department of Electronic Engineering and is affiliated with the Hamilton Institute and ALL Institute at Maynooth. Education BE in Computer Engineering – Trinity College Dublin PhD in Robotics – Trinity College Dublin MBA – University College Dublin Research Focus Professor Lacey’s research integrates robotics, real-time computer vision and human-machine systems with healthcare applications. His work spans assistive robotics for the elderly and visually impaired, augmented-reality surgical simulation, and technology-enabled infection prevention. Key themes include psychomotor learning in digital training tools, AI-driven hand-hygiene monitoring, and the design of user-centred healthcare technologies. Publication Trends Recent publications (2020-2021) concentrate on leveraging augmented reality and artificial intelligence to improve hand-hygiene compliance among healthcare workers, reflecting a translational trajectory from vision-based algorithms to large-scale hospital deployment. Earlier work (1995-2014) laid foundational contributions in mobility aids for the blind, endoscopic image enhancement, and robotic guidance systems. Awards & Recognition RESNA PVA Design Award for Robotics EU IST Award Irish Software Association Innovation Award Enterprise Ireland Technology Commercialisation Award Trinity College Innovation Award Entrepreneurship & Impact Professor Lacey has founded two university spin-outs: Haptica (2000), which created mobile healthcare robots and AR surgical simulators (acquired by CAE Healthcare in 2011), and SureWash (2010), whose hand-hygiene training systems are deployed internationally in hospitals. These ventures bridge academic research and clinical practice, securing real-world impact for his innovations. Laboratories & Collaborations He leads research activities within the Electronic Engineering Department and participates in interdisciplinary initiatives at the Hamilton Institute (systems modelling) and ALL Institute (assisted living and learning). His teams bring together engineers, healthcare professionals and industry partners to advance assistive and medical technologies.

• Robotics
• Real-time computer vision
• Human-machine systems
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Dr. Charles Markham is an Associate Professor in the Department of Computer Science at Maynooth University's Faculty of Science & Engineering. He graduated with a degree in Applied Physics from Dublin City University and earned his PhD in element specific imaging in computerised tomography. His research spans novel imaging systems, biomedical instrumentation, and human-computer interaction with a strong focus on brain-computer interfaces and motion capture technologies. Research Affiliations: Hamilton Institute, ALL Institute Teaching: Robotics, Computer Graphics, Advanced Computer Architecture Professor Markham's research interests center on novel imaging technologies including coded aperture imaging and wide-baseline stereo systems, motion capture and wearable computing with applications in rehabilitation, and mobile machine vision for driving simulation and augmented reality. His work with the Mathematics and Statistics Ecology group demonstrates interdisciplinary interests in ecological modelling . His publication record shows consistent contributions to brain-computer interfaces (2007-2011), driver behavior analysis (2014-2021), motion capture systems (2006-2009), and optical imaging techniques (2001-2008). The research spans multiple disciplines including neuroscience, biomedical engineering, and ecological mathematics. He has supervised several graduate students including D. Kelly (2009 thesis on sign language recognition) and J. Foody (2007 thesis on motion capture biofeedback systems). His collaborations extend across institutions with partnerships at TU Dublin and University College Dublin.

• Computer Science
• Biomedical Engineering
• Machine Vision
• +۵ مورد دیگر

Jim Buckley is a Professor in the Computer Science and Information Systems Department at the University of Limerick, Ireland, and a Principal Investigator in Lero. He leads the ARC research group focused on software evolution and legacy system modernization, with significant industry collaborations including Huawei, IBM, and Fidelity. Education: BSc in Biochemistry, University of Galway (1989) MSc in Computer Science, University of Limerick (1994) PhD in Computer Science, University of Limerick (2002) Research Focus: His work centers on AI-enhanced software engineering (AI4SE/SE4AI), featuring breakthroughs in clone detection, software architecture evaluation, and feature location. He has developed industry-adopted tools for software comprehension and evolution, with recent emphasis on explainable AI (XAI) and scalable neural network applications for industrial codebases. His research consistently bridges academic rigor with industrial implementation. Publication Trends: Recent articles (2022-2025) reveal a dominant shift toward AI-driven software engineering solutions, particularly in clone detection and architecture recovery. Key themes include industrial scalability, developer experience optimization, and responsible AI integration, with strong representation in top-tier venues like IEEE Transactions and ACM Computing Surveys. Scientific Awards: No awards specified in source material. Grants & Industry Impact: Leads the Huawei-funded TREES Programme and maintains active partnerships with 9+ companies. His research has yielded licensed tools (e.g., for legacy system evolution), two IP assignments from LLM-based clone detection work, and practical frameworks adopted by seven Irish enterprises. Research Infrastructure: Directs the ARC group within Lero, which combines academic researchers and industry practitioners to address real-world software maintenance challenges through empirical studies and tool prototyping.

• Software Engineering
• Software Evolution
• Artificial Intelligence for Software Engineering
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Dr. Derek Bridge is a Senior Lecturer in the School of Computer Science & Information Technology at University College Cork (UCC). With over 30 years of experience in AI research and education, he specializes in recommender systems and case-based reasoning. His work focuses on explanations in AI, promoting diversity and serendipity in recommendations, and developing interactive recommender systems. Founding member of the ACM Conference on Recommender Systems Combines research with research-led teaching, recognized for teaching excellence Affiliated with the Insight Centre for Data Analytics Scientific Awards: He has won multiple best paper prizes at ACM conferences and twice received teaching excellence awards.

• Artificial Intelligence
• Machine Learning
• Recommender Systems
• +۳ مورد دیگر

Prof. Mark Keane has served as Chair of Computer Science at University College Dublin since 1998. A cognitive psychology expert with a PhD from Trinity College Dublin, his career spans multiple institutions including the University of London, Open University, Cardiff University, and TCD. He has held leadership roles such as Director of ICT at Science Foundation Ireland (2004-2006) and Director General at SFI (2006-2007), overseeing €700M+ research investments. His work focuses on explainable AI, counterfactual reasoning, and sustainable agriculture applications. BA (UCD), PhD (TCD) in Cognitive Psychology Over 200 publications, H-index 45, 10,800+ citations Key advisor for Ireland's €3.7B Science, Technology & Innovation Strategy His research explores counterfactual explanations , semi-factual reasoning , and XAI in domains like dairy farming and climate resilience. Recent work combines machine learning with cognitive models to improve grass growth prediction and mastitis detection . He also investigates surprise theory through computational models. As Vice-President of Innovation & Partnerships at UCD (2007-2009), he drove academic-industry collaborations. Current affiliations include the Insight Centre for Data Analytics, where he leads AI research teams advancing case-based reasoning and deep learning integrations for explainable systems.

• Explainable Artificial Intelligence (XAI)
• Counterfactual Reasoning
• Machine Learning
• +۴ مورد دیگر

Dr. Derek Greene is an Assistant Professor at the School of Computer Science, University College Dublin, and a Funded Investigator at the Insight Centre for Data Analytics and the VistaMilk Research Centre. His research spans machine learning, natural language processing, and network analysis, with a focus on interdisciplinary applications in cultural analytics, smart agriculture, and political science. Dr. Greene has published over 60 research papers at international conferences and journals. His work includes developing methods for natural language processing , network analysis , and deep learning applied to diverse domains such as literary text mining, dairy industry monitoring, and political communication analysis. He leads projects integrating machine learning into cultural analytics, enhancing agricultural practices, and modeling policy agendas. The articles in his Google Scholar profile highlight a trend toward explainable AI , synthetic data generation , and network-based modeling . Key sub-fields include counterfactual explanations , transformer-based frameworks , temporal analysis of historical texts , and interdisciplinary knowledge transfer . His work bridges machine learning with applications in cultural studies , agriculture , and political science . Dr. Greene collaborates with institutions like the Insight Centre for Data Analytics and the VistaMilk Research Centre , integrating academic research with industry and policy needs. His funded investigator roles reflect ongoing support for applied research in data analytics and agricultural technology.

• Machine Learning
• Natural Language Processing
• Network Analysis
• +۳ مورد دیگر

Suchana Datta is a Research Fellow at the Insight Centre for Data Analytics . Her work bridges Information Retrieval and Artificial Intelligence , with a focus on query performance prediction (QPP) and causality-driven retrieval . She has contributed extensively to improving neural ranking models through relevance feedback and reproducibility studies. Research Highlights Developing novel frameworks for supervised and unsupervised QPP using deep learning and hybrid feature integration Advancing causality modeling in information retrieval systems Exploring temporal trends in 19th-century literature through computational analysis Pioneering work in cloud forensics with dynamic forensic frameworks Publication Trends Her recent work (2022-2025) emphasizes neural QPP models , reproducibility in IR experiments, and causality detection in query events. Earlier contributions (2016-2020) focus on cloud forensic frameworks like DCF and causal analysis in retrieval systems.

• Information Retrieval
• Natural Language Processing
• Digital Humanities
• +۳ مورد دیگر

Dr. Ramen Ghosh is a Researcher in the Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE) group at Atlantic Technological University, Sligo, where he has been working with Dr. Marion McAfee since July 2022. His research explores how complex systems behave when randomness, interaction, learning, and control intersect, with special focus on ergodicity principles. His academic background includes: PhD in Electrical Engineering, University College Dublin, Ireland (2018-2023) Master of Technology in Mathematics and Computing, Indian Institute of Technology Patna, India Master of Science in Mathematics, Chennai Mathematical Institute, India Bachelor of Science in Mathematics (Honours), Ramakrishna Mission Vidyamandira Belur Math, University of Calcutta, India Dr. Ghosh's research centers on ergodicity—the concept that a system's long-run behavior becomes independent of its initial state—and how this principle can fail, emerge, or be shaped through control and learning. His work spans nonlinear systems, iterated function systems, dynamic mode decomposition, and applications in power grids, environmental systems, and materials science. He approaches complex system behavior through the intersection of randomness, interaction, learning, and control mechanisms. His publication record shows consistent growth with 1 article in 2022, 4 in 2023, 1 in 2024, and 1 in 2025. His research demonstrates strong interdisciplinary connections between theoretical mathematics and practical applications across environmental science, materials engineering, and control systems. The fingerprint analysis of his work reveals significant contributions to Nonlinearity, Iterated Function Systems, Dynamic Mode Decomposition, and Stable State mathematics. Dr. Ghosh has teaching experience including MATH09010 - Introduction to Mathematical and Computational Modelling at Atlantic Technological University (2022), and multiple offerings of EEEN30150-Modelling and Simulation and EEEN30020-Circuit Theory at University College Dublin (2019-2021). His research activities include presentations on ergodicity, predictability, fairness, and control for societal-scale challenges.

• Complex Systems
• Ergodicity
• Control Theory
• +۵ مورد دیگر