جست‌وجوی استاد و پژوهشگر

Jahan Zeb Gulمشاهده پروفایل

استادیار

• Soft Robotics
• Embedded AI
• Soft Sensors/Actuators
• +۲ مورد دیگر

Dr. Jahan Zeb Gul is an Assistant Professor in Robotics and AI at Maynooth University's Department of Electronic Engineering within the Faculty of Science & Engineering. His research focuses on integrating machine learning techniques with soft robotics to develop adaptive intelligent systems for biomedical applications and dynamic environments. BS in Electrical Engineering (Computer Engineering specialization) from UET Taxila, Pakistan (2013) MS leading to PhD in Mechatronics Engineering from Jeju National University, South Korea (fully funded scholarship) His work spans Soft Robotics , Embedded AI , Soft Sensors/Actuators , and Biomedical Devices , emphasizing the intersection of robotics and artificial intelligence. He has reviewed over 50 funding proposals and secured research grants from the Pakistan Science Foundation, National Centre of Robotics and Automation (NCRA), and National Centre of Artificial Intelligence (NCAI). Scientific contributions include 100+ international certifications in AI/robotics, 1000+ citations, and leadership in research fund reviewer training. He serves as an external reviewer for Swiss research grants and Pakistani scientific institutions. Contact details: Email: JahanZeb.Gul@mu.ie, jahanzeb.gul@mu.ie Location: Eolas Building, Engineering Floor, Room 205

Gerard Laceyمشاهده پروفایل

استاد

• Robotics
• Real-time computer vision
• Human-machine systems
• +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.

Charles Markhamمشاهده پروفایل

دانشیار

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

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.

Suzanne Littleمشاهده پروفایل

استادیار

• Multimedia Semantics
• Artificial Intelligence
• Machine Learning
• +۲ مورد دیگر

Dr. Suzanne Little is an Assistant Professor in the School of Computing at Dublin City University and an SFI Funded Investigator within the Insight Centre for Data Analytics. She also serves as Co-Director of a research initiative at DCU. Her research centers on multimedia semantics , leveraging artificial intelligence, machine learning, computer vision, and information retrieval to advance content-based media analytics. This work focuses on developing intelligent systems that extract semantic meaning from multimedia content through interdisciplinary computational approaches. As an SFI-funded researcher, Dr. Little contributes to Ireland's national data analytics infrastructure through the Insight Centre. Her Co-Director role demonstrates active leadership in research program development and execution at DCU. She is embedded within the Insight Centre for Data Analytics, a major collaborative research environment driving innovation in data science applications across multiple sectors.

Jim Buckleyمشاهده پروفایل

استاد

• Software Engineering
• Software Evolution
• Artificial Intelligence for Software Engineering
• +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.

Nadeem Ratherمشاهده پروفایل

پژوهشگر ارشد

• Electromagnetic Systems
• RF Technologies
• AI Algorithms
• +۳ مورد دیگر

Nadeem Rather is a Research Fellow at the Wireless Communications and AI Research Lab, Tyndall National Institute, University College Cork (UCC), Ireland, where he has conducted research since 2019. His work focuses on developing AI-driven electromagnetic systems with emphasis on RF technologies and intelligent antenna design. His academic background includes: Bachelor’s degree in Electronics and Communication Engineering Research Master’s degree in Communication Systems PhD from University College Cork (2024) Dr. Rather’s research integrates advanced AI algorithms with electromagnetic systems to optimize RF components for emerging IoT applications. His work spans chipless RFID, NFC sensor networks, and adaptive antenna design, addressing challenges in spectrum efficiency, robust detection, and practical implementation across agriculture, healthcare, and cultural heritage domains. He bridges theoretical electromagnetic modeling with real-world sensor deployment. His publication trend reveals a concentrated focus on machine learning for electromagnetic systems, particularly in chipless RFID and NFC applications. Recent works demonstrate innovative approaches to spectrum utilization, tag design, and robust detection techniques using deep learning architectures like U-Net, with significant contributions to agricultural monitoring, museum preservation, and animal health tracking. His scientific achievements have been recognized through: Best Application of AI in a Student Project (AI Awards Ireland) Wrixon Research Excellence Bursary Postgraduate Publication of the Year Awards (2020, 2023) Best Student Research Paper, International Workshop on Antenna Technology (2021) Best Demonstration Award, VistaMilk Conference (2023) As an active IEEE Member, Dr. Rather contributes to the Wireless Communications and AI Research Lab’s mission of advancing electromagnetic systems through AI. His current projects include transparent epidermal antennas for human-centric IoT and battery-less NFC sensors for health monitoring, with demonstrated impact in cattle health tracking and museum artifact preservation.

• Quantum Optical Communications
• Free Space Optical Communications
• Machine Learning Applications
• +۳ مورد دیگر

Dmitrii Briantcev is a Researcher at the CONNECT Centre, Trinity College Dublin, working on the IrelandQCI project in Quantum Optical Communications since June 2023. He holds a Bachelor's in Radiophysics from Saint Petersburg State University (2018) and MS/PhD in Electrical and Computer Engineering from KAUST, where his research focused on Machine Learning and Physical Simulations for Free Space Optical (FSO) communication systems. His educational background: Bachelor in Radiophysics, Saint Petersburg State University (2018) MS and PhD in Electrical and Computer Engineering, King Abdullah University of Science and Technology (KAUST) Dmitrii's research spans optical and quantum communications domains. His current IrelandQCI project involves building national quantum communication infrastructure, while prior PhD work developed machine learning models for FSO reliability. His broader interests integrate Cybersecurity, Satellite Communications, and Smart Cities applications in next-generation networks. As part of CONNECT's quantum communications team, he contributes to Ireland's quantum testbed development. No information is available regarding advisory roles, grants, or scientific awards.

• Photonic Integrated Circuits
• Optical Performance Monitoring
• Machine Learning

Olivia Butler is a CONNECT PhD researcher at Trinity College Dublin, supervised by Dr. Aleksandra Kaszubowska-Anandarajah. Her work focuses on optical performance monitoring for future network technologies using advanced photonic systems. Education: B.A.I in Electronic and Computer Engineering from Trinity College Dublin Research Interests: Olivia specializes in Photonic Integrated Circuits , with expertise in Optical Monitoring and Machine Learning applications for network optimization. Her doctoral research explores adaptive monitoring frameworks for customized optical networks. Projects: Previously worked on the DTIF iLife project, focusing on static characterization and calibration of photonic integrated circuits for next-generation laser systems.

• Data Science
• Machine Learning
• Functional Data Analysis
• +۵ مورد دیگر

Autumn O’Donnell is a Postdoctoral Researcher at the Insight Centre for Data Analytics, focusing on functional data analysis for cardiac output prediction in a project led by Dr. Andrew Simpkin. PhD in Transcriptomics and Machine Learning for Prostate Cancer Recurrence Prediction at University College Cork MSc in Data Science and Analytics from University College Cork (2021) BEng in Biomedical Engineering from Munster Technological University (formerly Cork Institute of Technology) PGCert in Perfusion Science from University of Bristol Her research bridges Data Science , Machine Learning , and Biomedical Engineering , targeting applications in Cardiovascular Medicine and Cancer Research . She specializes in integrating computational methodologies with clinical data analysis.

• Semantic Web
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Dr. Asma Slaimi is a Postdoctoral Researcher at the School of Electronic Engineering , Dublin City University (DCU) , Ireland. She previously completed her PhD and Master’s at DCU and The Insight Centre for Data Analytics, respectively. Current research focuses on applying AI and Machine Learning to the water domain in collaboration with Arup. Key research areas include Semantic Web, Ontology-based Named Entity Recognition, and E-Recruitment systems. Collaborators: Prof. Noel O’Connor, Dr. Fiona, Dr. Michael, Dr. Susan Hegarty.

• Data Analytics
• Machine Learning
• Neural Engineering
• +۶ مورد دیگر

Tomas Ward is the AIB Chair of Data Analytics at the School of Computing, Dublin City University , and a member of the Insight Centre for Data Analytics funded by Science Foundation Ireland. Education B.E. in Engineering (1994) M.Eng.Sc. in Engineering (1996) Ph.D. in Engineering (2000) His research focuses on understanding human health, performance, and decision-making through physiological and behavioral sensing. Key areas include data analytics, neural engineering, and mobile health technologies. Notable Contributions Licensing e-health sensor streaming technologies Development of over-the-air programming systems Advocacy for hacker spaces and co-founding Dublin Maker He has authored over 240 peer-reviewed publications and actively bridges entrepreneurship with academic research.

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

• Bayesian Methods
• Statistics
• Machine Learning
• +۳ مورد دیگر

Simon Wilson is Professor of Statistics at Trinity College Dublin and serves as Principal Investigator of the Machine Learning & Statistics research group. He is affiliated with the university’s School of Computer Science and Statistics. Education: PhD in Stochastic Modeling, George Washington University, Washington DC (1993) Research Focus: His work centres on the development and application of Bayesian statistical methods to problems in reliability, ecology, and astronomy, bridging theoretical advances with real-world scientific challenges. Contact: simon.wilson@insight-centre.org , Tel. +353 1 896 1759.

• Personalised Nutrition
• Human Nutrition
• Dietary Interventions
• +۵ مورد دیگر

Associate Professor Eileen Gibney is a faculty member in the School of Agriculture and Food Science at University College Dublin (UCD), serving as Deputy Director of the UCD Institute of Food and Health and Director of Executive Education. She is a Funded Investigator with the Insight Centre for Data Analytics and contributes to the BSc Human Nutrition program. Her educational background includes: BSc in Human Nutrition from Ulster University PhD from the Dunn Nutrition Unit, University of Cambridge (2001) MSc in Molecular Medicine from Trinity College Dublin (2003) Professor Gibney's research centers on personalised nutrition , investigating inter-individual variation in dietary responses and developing innovative technologies for personalised dietary feedback. Her work spans sustainable diets , dairy science , and cardiometabolic health , often through large-scale intervention studies like MyPlanetDiet and Food4Me. She integrates environmental sustainability with nutritional science, focusing on portion size standardization and digital dietary assessment tools. Her recent publications (2024-2025) demonstrate leadership in sustainable diet research, dairy product health impacts, and AI applications in nutrition. Key trends include methodological innovations for global dietary guidelines, evaluation of dairy matrices on cholesterol metabolism, and development of culturally adapted digital tools like Foodbook24 for diverse populations. She has secured major funding as Principal Investigator for: Food4Me: Pan-European personalised nutrition intervention Food for Health Ireland: National food research consortium Insight Centre: Data analytics for nutrition and health FNS-Cloud: Framework for dietary data reuse Professor Gibney serves on the Public Health Nutrition sub-Committee of the Food Safety Authority of Ireland and is a Trustee of the Nutrition Society of UK and Ireland. She previously served as Associate Dean of Teaching and Learning (2015-2019) and Director of the Irish Association for Clinical Nutrition and Metabolism (2010-2019).

• Machine Learning
• Natural Language Processing
• Network Analysis
• +۳ 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.