Find Academic Supervisors

Shane GilroyView profile

Lecturer

• Autonomous Vehicles
• Image Sensors
• Automotive Engineering
• +3 more

Shane Gilroy is a Lecturer in Electronic Engineering at the Department of Mechatronic Engineering, ATU Sligo. His research focuses on automotive systems, particularly autonomous vehicles, image sensor technology, and object detection challenges in occluded environments. He actively contributes to improving road safety through advancements in pedestrian detection, sensor validation, and cybersecurity in connected vehicles. His work aligns with UN Sustainable Development Goals, emphasizing innovation in urban mobility and sustainable infrastructure. Gilroy’s expertise spans computer vision, robotics, and automotive engineering, with notable contributions to occlusion classification methods and lifecycle validation of automotive components. He is currently accepting PhD students to further explore these interdisciplinary areas. Key research themes include: Autonomous vehicle perception systems Occlusion challenges in road safety Image sensor performance optimization Cybersecurity for connected vehicles Lean manufacturing methodologies His publications demonstrate a strong emphasis on practical applications, from improving pedestrian detection algorithms to evaluating sensor reliability under real-world conditions. Recent work explores urban mobility solutions and the integration of machine learning models for occlusion analysis.

• Medical Imaging
• Deep Learning
• Transesophageal Echocardiography
• +5 more

Siobhan Moane is a researcher actively contributing to Medical Imaging , Pharmacology , and Sports Science , with work aligned to the United Nations Sustainable Development Goals (SDGs). Her recent research focuses on Deep Learning applications in Transesophageal Echocardiography (TEE) and Computed Tomography (CT) for cardiac and urological diagnostics, as well as Augmented Reality integration in ultrasound-guided procedures. Moane also explores pharmacological properties of natural compounds for antimalarial and antitrypanosomal therapies through in vitro and in silico studies. Key trends in her publications include AI-driven biomedical imaging (2025: 4 articles), machine learning for segmentation tasks , and clinical applications of imaging technologies . In Sports Science (2024), she conducted a systematic review on load monitoring tools in Gaelic sports. Collaborative efforts span institutions like the University of Cape Coast and University of KwaZulu-Natal , reflecting her interdisciplinary and global approach.

• Robotics
• Sensor Fusion
• Machine Learning
• +2 more

Dr. Aubrey James Roche is Lecturer in Robotics and Automation at ATU Sligo's School of Engineering, with visiting researcher status at Loughborough University London. He holds a PhD in Multimodal Machine Learning and MSc in Digital Technologies. His research develops perception systems for autonomous vehicles using LiDAR, computer vision, and sensor fusion. Applications include intelligent mobility solutions, human activity recognition, and robotic navigation. Recent work focuses on dementia screening tools deployable on edge devices. Roche maintains professional affiliations with IEEE and Engineers Ireland. Before academia, he worked as a forensic engineer and project engineer in transportation and pharmaceutical sectors.

• Biomedical Image Processing
• Machine Learning
• Computer Vision
• +1 more

Saritha Unnikrishnan is Lecturer in Computing at Atlantic Technological University (ATU) Sligo, Ireland, affiliated with the Department of Computer & Electronic Engineering. She serves as Principal Investigator at Health and Biomedical Research Centre (HEAL) and Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE). Her research develops AI and machine learning solutions for biomedical challenges including tumor characterization from MRI, microplastic analysis, and educational chatbot systems. Key methodologies include deep learning architectures, graph neural networks, and hyperspectral image processing applied to medical diagnostics. Recent work includes explainable AI models for glioma grading, nanoparticle characterization in industrial emulsions, and comparative studies of chatbot platforms for student FAQs. Publications appear in high-impact journals including International Journal of Pharmaceutics and Journal of Magnetic Resonance Imaging.

Marion McAfeeView profile

Senior Lecturer

• Control Systems
• Additive Manufacturing
• Machine Learning
• +2 more

Marion McAfee is a Senior Lecturer in Systems and Control Engineering at Atlantic Technological University. She co-directs the MISHE Centre and leads projects in sustainable manufacturing, AI applications, and sensor technologies. Her research integrates machine learning with real-time process control. Key initiatives include PROCEED 3D for personalized drug delivery devices and iGREENPHARM for sustainable pharmaceutical manufacturing.

Adam TothView profile

Associate Professor

• Biomechanics
• Neuroscience
• Sensory Motor Control
• +7 more

Adam Toth is an Associate Professor in biomechanics and neuroscience at the University of Limerick, affiliated with the Department of Physical Education & Sport Sciences. He serves as programme manager of the Esports Science Research Lab within Lero – the Irish Software Research Centre, and is a member of the Sports and Human Performance Research Centre and Health Research Institute. His work intersects human physiology, cognitive neuroscience, and gaming analytics. Adam earned his PhD in neurophysiology and biomechanics from the University of Guelph, Canada. His research focuses on sensory motor control in esports athletes, cognitive benefits of action video gaming, balance mechanisms in aging populations, and neurostimulation techniques like galvanic vestibular stimulation and tDCS to enhance motor learning. His publications highlight expertise in esports biomechanics, AI-driven performance prediction, and cognitive fatigue studies. Collaborations span neuroscience, sports science, and software engineering. He lectures on modules including SS4312 and BR4071, and has presented internationally at TEDx events.

• Genetic Programming
• Evolutionary Algorithms
• Combinatorial Optimisation
• +6 more

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.

Gerard LaceyView profile

Professor

• Robotics
• Real-time computer vision
• Human-machine systems
• +3 more

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 MarkhamView profile

Associate Professor

• Computer Science
• Biomedical Engineering
• Machine Vision
• +5 more

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 LittleView profile

Assistant Professor

• Multimedia Semantics
• Artificial Intelligence
• Machine Learning
• +2 more

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.

Kevin MeehanView profile

Lecturer

• Computer Vision
• Machine Learning
• Ubiquitous Computing
• +3 more

Dr. Kevin Meehan serves as a Lecturer in Computing at Atlantic Technological University (ATU) in Ireland, holding dual roles as Principal Investigator for both WisarLab and the Centre for Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE). His academic foundation includes a BSc Hons and PhD in Computer Science from Ulster University, complemented by an MA in Learning & Teaching and a PGCE in Further and Higher Education. His research spans Computer Vision , Machine Learning , and Ubiquitous Computing , with significant contributions in trajectory prediction, immune response modeling, and environmental monitoring systems. Recent publications demonstrate expertise in BiLSTM networks, graph neural networks, and DenseNet applications for real-world problem solving. Notable professional recognition includes Fellowship in the Higher Education Academy. His work aligns with UN Sustainable Development Goals through technological solutions for health and environmental challenges. As an educator, he teaches Machine Learning, Computer Vision, and Data Science while leading industry collaborations with over 45 SMEs. His research has secured €400,000+ in funding for knowledge transfer projects, demonstrating strong industry-academia linkage.

• Medical Imaging
• Educational Technology
• Affective Computing
• +5 more

JIA Xibin serves as a full Professor and doctoral/master's thesis supervisor at Beijing University of Technology's Faculty of Information Technology and Dublin International College. She holds editorial responsibilities for the TIIS journal and maintains active memberships in the China Computer Federation (CCF) and China Society of Image and Graphics (CSIG), including specialized committees for Machine Vision and Big Video Data. Her educational foundation spans a B.S. in Wireless Technology from Chongqing University (1991), M.S. in Measuring and Testing Technology from North University of China (1996), and Ph.D. in Computer Application Technology from Beijing University of Technology (2007). International experience includes visiting scholar positions at University of California Riverside (2015) and Flinders University (2009). Research focuses on intelligent medical imaging for liver disease diagnosis, affective computing in educational contexts, and cognitive behavior modeling through multimodal fusion techniques. Her methodology integrates representation learning with transfer and few-shot learning paradigms to address data scarcity in medical applications. Current publications demonstrate consistent focus on domain adaptation and medical image analysis , with significant contributions to multimodal MRI interpretation for non-alcoholic fatty liver disease and hepatocellular carcinoma. Her work bridges theoretical machine learning with clinical applications through deep neural network architectures. Active research leadership includes principal investigator roles for: National Natural Science Foundation grant on non-invasive liver disease assessment (2019-2022) Beijing Natural Science Foundation project on campus safety risk prediction (2020-2022) These projects emphasize big data analytics for healthcare and educational safety systems, reflecting her dual expertise in technical innovation and practical implementation.

Hamail AyazView profile

Lecturer

• Computer Vision
• Artificial Intelligence
• Medical Imaging
• +1 more

Hamail Ayaz serves as an Assistant Lecturer in Computing at Atlantic Technological University (ATU) Sligo, specializing in AI-driven computer vision while concurrently completing his PhD in the School of Computing at ATU, where his research focuses on eXplainable AI applications for diagnosing glioma brain tumours. His educational background includes: Bachelor of Computer Science (with distinction) from COMSATS University Islamabad Master of Computer Engineering investigating advanced imaging protocols and generative adversarial networks for food processing applications Hamail's research bridges computer vision and artificial intelligence with practical healthcare diagnostics and industrial applications, demonstrating particular expertise in medical imaging analysis and machine learning implementation across diverse domains including neuro-oncology and food technology sectors. He actively contributes to the STEM Passport initiative promoting women in STEM fields across Ireland, with his scholarly impact evidenced through publications in high-impact journals despite no specific advising roles or research grants being documented in available sources. As an integral member of ATU Sligo's School of Computing research ecosystem, Hamail collaborates on advancing AI-driven computer vision solutions while maintaining strong connections to both Pakistani academic roots and Irish technological innovation initiatives.