Find Academic Supervisors

• Robotics
• Intelligent Systems
• Unmanned Aerial Vehicles (UAVs)
• +7 more

Petar Trslić is an Assistant Professor at the University of Limerick's School of Engineering, affiliated with the Centre for Robotics and Intelligent Systems. His research focuses on advanced robotics, autonomous systems, and sensor fusion technologies, with applications in maritime operations, wildlife monitoring, and infrastructure inspection. Key technical areas include Unmanned Aerial Vehicles (UAVs), Remotely Operated Vehicles (ROVs), path planning algorithms, and LiDAR-based systems. His work contributes to UN Sustainable Development Goals related to innovation and infrastructure, climate action, and sustainable energy. Trslić has collaborated internationally on projects involving cooperative robotic systems, multi-sensor fusion for state estimation, and autonomous vehicle coordination in challenging environments. His recent publications highlight innovations in UAV wildlife surveillance, maritime robotics for offshore wind farms, and automated infrastructure inspection using 3D reconstruction. He has secured research funding for initiatives in autonomous underwater robotics and has developed novel algorithms for robotic docking and navigation under dynamic conditions. Trslić's lab emphasizes practical solutions for industrial automation challenges and environmental monitoring through interdisciplinary approaches.

• Robotics
• Intelligent Systems
• Underwater Robotics
• +3 more

Anthony Weir is a researcher at the Department of Electronics & Computer Engineering, University of Limerick, affiliated with the Centre for Robotics and Intelligent Systems. His work focuses on underwater robotics, control systems, and marine engineering applications. Role: Researcher Institution: University of Limerick Department: Electronics & Computer Engineering Research Interests: Specializing in Remotely Operated Vehicles (ROVs) and autonomous underwater systems , his research addresses challenges in offshore wind farm inspection, ship hull repair, and robotic manipulation. Key technologies include visual servoing , inverse kinematics , and friction stir welding . Recent Publication Trends (2023-2024): Recent work demonstrates advancements in autonomous visual inspection , path planning algorithms , and underwater repair systems . Collaborative projects with engineers like Santos, Omerdic, and Toal highlight applications in offshore wind turbines and damaged ship hulls. Collaborations: Active collaborations span marine robotics, control systems, and renewable energy engineering, with frequent contributions to IEEE-conference proceedings and journals like IEEE Access and Journal of Intelligent and Robotic Systems .

• Ageing
• Dementia
• Palliative Care
• +10 more

Assoc Professor Sarah Donnelly is an Associate Professor of Social Work at the School of Social Policy, Social Work and Social Justice , University College Dublin. Her career spans clinical practice, research, and academic leadership, with a focus on ageing, dementia, and adult safeguarding. She coordinates UCD's Ageing Network and advises the Irish Association of Social Workers on adult safeguarding. Education : BSocSc (Trinity College Dublin), PhD (Trinity College Dublin). Appointments : Assistant Professor (2014-2024), promoted to Associate Professor in 2024. Research and Practice : Sarah's work addresses interprofessional collaboration , carer harm , advance care planning , and ethical implications of care robotics . She emphasizes human rights, participatory methodologies, and policy reform. Her Orcid profile highlights 167 publications. Recent Publications : Her 2025-2024 articles analyze interprofessional collaboration in community care, carer harm in dementia, ethical robotics, and coercive control in family caregiving. These studies span European , Irish , and cross-cultural contexts , often involving co-design with stakeholders. Awards : Willie Bermingham Memorial Medal 2024 for human rights work; Geary Fellow 2016 . Teaching : Coordinates modules in Research Methods , Placement Education , and Preparation for Professional Practice . Serves on UCD's Human Research Ethics Committee and Teaching and Learning Committee . Leadership : Director of Practice Learning and Global Engagement at UCD (2024), Co-Director of Professional Masters in Social Work (2018-2021).

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.

• Machine Learning
• Deep Learning
• Time Series Data Analysis
• +5 more

Michael Madden is the Established Professor and Head of the School of Computer Science at the University of Galway. He founded the Machine Learning Research Group in 2001 and focuses on theoretical advances in machine learning applied to medicine, engineering, and physical sciences. His work includes deep learning with virtual data augmentation, dynamic Bayesian networks for ICU monitoring, and probabilistic analytics for time series analysis. Research Areas: Machine Learning, Algorithms, Bayesian Networks, Reinforcement Learning, Time Series Analysis Applications: Healthcare (ICU monitoring, gene expression), Engineering, Physical Sciences Industry Collaborations: Hewlett Packard Enterprise, Valeo, IBM, University Hospital Galway Scientific Awards 9 publication awards

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.