Dr. Niall Murray is a Senior Lecturer in the Department of Computer and Software Engineering within the Faculty of Engineering and Informatics. His research focuses on enhancing user experiences through immersive technologies and quality-of-experience measurement frameworks. His scholarly work spans virtual/augmented reality systems, multimedia quality assessment, and human-computer interaction paradigms. Recent investigations explore physiological signal analysis for experience evaluation and accessible computing solutions. Publications demonstrate consistent focus on optimizing extended reality applications across domains including education, industrial design, and assistive technology. Research outputs frequently incorporate multimodal interfaces and machine learning approaches.
Professor Denis O'Dwyer is affiliated with the Faculty of Engineering and Informatics at an unspecified university, specifically within the Department of Trades . His research focuses on enabling smart cities through vehicle telematics, aligning with UN Sustainable Development Goals related to urban sustainability and environmental protection. Research Interests : Smart cities, fuel economy optimization, carbon dioxide reduction, and IoT-based sensor data systems. Key Contribution : Co-authored a 2020 study in IEEE Sensors Journal analyzing how vehicle telematics can support sustainable urban infrastructure. The research output highlights interdisciplinary work spanning computer science, engineering, and transportation policy, with a current h-index of 15 based on Scopus citations.
Dr. Amin Abbasi is a researcher at Universiti Teknologi PETRONAS , affiliated with the College of Sciences . His work focuses on polymer chemistry, sustainable materials, and environmental applications. Key research areas include developing novel polymers for wastewater treatment, biodegradable composites, and green chemical processes. His studies on inverse vulcanized copolymers and their applications in mercury removal, plasticizers, and fertilizer coatings highlight his contributions to sustainable chemistry. Collaborations with institutions like the University of Wah and Technological University of the Shannon have advanced his work in material science and environmental engineering. Research Interests: Design of sulfur-based polymers for environmental remediation Biodegradable polymer blends and composites Machine learning for materials science Green synthesis of value-added materials from waste oils/chemicals Recent Contributions: His 2025 study on TPS/PLA compatibilization advances biodegradable material design. The 2024 work on amine-functionalized polysulfides demonstrated breakthroughs in mercury adsorption. He also pioneered the use of inverse vulcanization for creating sustainable polymers from vegetable oils, addressing both material science and environmental challenges. Grants & Collaborations: Active in interdisciplinary projects spanning polymer engineering, environmental chemistry, and computational modeling. His work aligns with UN SDGs 6 (Clean Water) and 9 (Industry Innovation).
Paul Greaney is a Lecturer in Computing at Atlantic Technological University, affiliated with the Department of Computing. He is a Principal Investigator in the Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE) research unit. His work aligns with UN Sustainable Development Goals, particularly in advancing technologies for environmental and health applications. Greaney holds an h-index of 38 with over 2025 citations, reflecting his research impact. Research interests span machine learning, artificial intelligence, IoT security, and materials science. His recent projects include pedestrian trajectory prediction using neural networks, resume parsing with BERT-based models, and IoT trustless environments. He has also contributed to studies on dielectric membranes and quantum dot cytotoxicity. Greaney’s publications emphasize interdisciplinary approaches, blending computational methods with real-world applications. His work on spatial-temporal attention models and generative frameworks demonstrates expertise in AI-driven solutions for complex systems. No advising or grant details are provided in the text. He is part of the MISHE team, focusing on mathematical modeling and intelligent systems for societal challenges.
Shagufta Henna is a Lecturer in Computer Science at the Department of Computing, Atlantic Technological University. Her research focuses on machine learning applications in wireless sensor networks, IoT systems, cybersecurity, and environmental monitoring. She contributes to UN Sustainable Development Goals through projects addressing environmental sustainability and health. Her expertise includes federated learning for malware detection in healthcare IoT, deep learning optimization for sensor networks, explainable AI for water quality prediction, and ensemble methods for human activity recognition. Recent work highlights include: Developing graph neural networks for IoT-based healthcare cybersecurity Accelerating environmental monitoring via deep learning in uncontrolled sensor networks Deploying SHAP-based XAI for water quality prediction interpretability No scientific awards explicitly listed. Research output includes 45 publications across journals and conferences, with recent contributions in Results in Engineering and IEEE proceedings. Active collaborations span international institutions focusing on AI-driven environmental and healthcare solutions.
Dr. Liam Brown is the Vice-President of Research, Development, and Innovation at Midwest Research, Development and Innovation. His work spans multiple disciplines, with a primary focus on Machine Learning , Deep Learning , and Computer Science . He contributes to fields such as Process Planning , Enterprise Performance Optimization , and Neural Networks .
Dr. Cian Taylor is a Lecturer in Statistics within the Department of Environmental Science at Atlantic Technological University. His research focuses on developing advanced optical sensors using surface plasmon resonance technology, particularly for environmental hydrogen detection applications. Dr. Taylor's theoretical and experimental work involves nanomaterial synthesis, fiber optic design, and computational modeling of sensor performance. His publications demonstrate expertise in optimizing sensor architectures for industrial and environmental monitoring purposes.
Dr. Muhammad Mahmood Ali is a Principal Investigator at the Precision Engineering Materials and Manufacturing Research Centre (PEM Research Centre) and holds an affiliation with the Department of Mechatronic Engineering at Atlantic Technological University. His research spans metamaterials, nanotechnology, biomedical engineering, and materials science, with a focus on applications in energy, sensors, and sustainable materials. Dr. Ali has contributed to over 93 publications, with a citation count of 2,430 and an h-index of 27, reflecting significant academic impact. His work aligns with UN Sustainable Development Goals, particularly in advancing clean energy and sustainable infrastructure. His research interests include metamaterials design, nanocomposite synthesis for biomedical uses, and thermal engineering applications. Notable contributions include studies on fibre optic sensors, electrocatalysts for hydrogen generation, and cementitious materials' behavior under accelerated curing. Dr. Ali’s recent work explores green energy solutions through hydrothermal liquefaction of waste and neural network-driven fluid flow modeling. Dr. Ali’s articles highlight interdisciplinary approaches, blending materials science with computational methods and renewable energy technologies. His research often addresses practical challenges in manufacturing, sensor technology, and environmental sustainability. While no specific awards are listed, his extensive publication record underscores his active role in advancing engineering and materials science. He has been involved in collaborative projects on global scales, focusing on areas such as microchannel heat exchangers, antimicrobial nanomaterials, and laser-based manufacturing. His lab, the PEM Research Centre, emphasizes precision engineering and innovative material solutions. No specific grants or student advisees are detailed in the provided information.
Maryna Lishchynska is a Lecturer in the Department of Mathematics at Munster Technological University (MTU). She specializes in teaching mathematics across Level 8 Engineering programmes, including Mechanical, Biomedical, Chemical, and Structural Engineering at years 2, 3, and 4. Holding a PhD in Engineering and an MSc in Applied Mathematics, her research focuses on third-level mathematics education and computational modeling. Her educational background includes a Master's in Applied Mathematics and a Doctorate in Engineering, reflecting her interdisciplinary expertise. Her research bridges educational theory and practice, with a recent emphasis on student motivation, self-concept, and digital learning resources in mathematics education. Earlier work explored computational modeling in micromechanical systems and behavioral analysis. Publications highlight trends in service mathematics modules, pandemic-era teaching challenges, and student perceptions of digital tools. Her collaborations include projects like the Transposition Initiative, investigating equation manipulation and peer learning dynamics. Though no awards or grants are explicitly mentioned, her active research and teaching roles underscore her contributions to mathematics education innovation. Maryna collaborates with colleagues such as C. Palmer, D. O’Connor, and V. Morari on pedagogical research. Her work addresses both practical classroom strategies and broader systemic issues in mathematics education, particularly in non-specialist contexts.
Frank Doyle is a Lecturer in the Department of Electrical and Electronic Engineering at the Faculty of Engineering and the Built Environment. His work focuses on research and development within energy engineering, precision systems, and Industry 4.0 applications. He has contributed to sustainable design and manufacturing efficiency, aligning with UN Sustainable Development Goals. His research interests include optimizing energy conservation in industrial facilities, sensor networks for precision engineering, and leveraging IoT and interoperability standards to enhance manufacturing processes. Doyle has collaborated extensively with colleagues such as Dr. Cosgrove and Dr. Carvalho on projects related to predictive maintenance and digitization in SME environments. Notable contributions include studies on behavioral-driven energy savings in manufacturing and the digitization of shop-floor operations. His research outputs span conference articles and contributions, emphasizing practical applications of digital technologies and data-driven approaches to improve industrial efficiency. Frank Doyle’s academic profile reflects a commitment to advancing manufacturing and energy systems through innovative technical solutions, with a particular emphasis on bridging theoretical research and real-world industrial challenges.
Joseph Sullivan is a Lecturer in the Department of Electrical and Electronic Engineering at the Faculty of Engineering and the Built Environment. His research focuses on Machine Learning, Evolutionary Algorithms, and their applications in optimizing systems such as grammatical evolution and digital circuits. His work contributes to the UN Sustainable Development Goals, particularly in advancing technological solutions for efficient hardware and software systems. Key research trends include enhancing algorithmic performance through adaptive selection methods, improving modularity in code via leap mapping techniques, and integrating fuzzy logic with genetic programming for classification tasks. Sullivan’s publications emphasize practical applications of evolutionary computation in solving complex engineering problems. No scientific awards or grants are explicitly listed, but his h-index of 89 reflects significant scholarly impact. He has advised no listed students, and his research is part of collaborative efforts within the faculty’s engineering research groups.
Dr. Luan Trinh is an Assistant Lecturer in the Department of the Built Environment at the Faculty of Engineering and the Built Environment. His research focuses on structural mechanics, composite materials, and advanced computational methods. Key areas include buckling analysis of cylindrical shells, vibration behavior of porous microbeams, and the application of modified couple stress theory in size-dependent structural analysis. He employs numerical techniques such as state-space approaches and inverse differential quadrature for modeling complex engineering systems. His work contributes to sustainable development goals through advancements in material science and structural optimization. Research interests include structural stability, composite materials, and finite element analysis. Recent studies emphasize the dynamic and static responses of functionally graded beams, porous microstructures, and elastically supported systems. Collaborations span international institutions, particularly in composite materials and mechanical behavior modeling. Publications highlight innovations in beam theories, buckling modes, and probabilistic analysis, often addressing practical engineering challenges such as compression buckling and boundary condition effects. While no specific grants or advisees are listed, his contributions are reflected in over 560 citations and an h-index of 11, underscoring impactful research in structural and materials engineering.
Trevor Clohessy is a Lecturer in Engineering and Principal Investigator at the Business Research Innovation Network Group (BRING). His research focuses on Blockchain Technology, Digital Transformation, and Cloud Computing, with contributions to Sustainable Development Goals (SDGs) related to innovation and infrastructure. He holds affiliations in the Department of Mechanical & Industrial Engineering and has authored over 24 peer-reviewed publications. Key research areas include blockchain adoption in supply chains, cloud computing's impact on IT service providers, and threshold concepts in information systems education. He has collaborated internationally, particularly in studies analyzing blockchain's role in fisheries, healthcare, and smart cities. His recent work (2023–2024) explores blockchain's integration into supply chains, smart city frameworks, and behavioral impacts of technology on work and health. Notable publications include a blockchain research agenda for smart cities and a dualistic passion model for mobile gambling harm minimization. Scientific Contributions: Over 695 citations and an h-index of 8. Professional Activities: Organized the 2023 Sustainable Innovation with Blockchain conference. Labs/Teams: Leads research through the BRING group, focusing on technology adoption and digital transformation.
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.
Marie Therese Hume is a Lecturer in the Department of Computer & Electronic Engineering at Atlantic Technological University Sligo. Her research focuses on technological change, science and technology studies, and education for sustainable development. She contributes to the UN Sustainable Development Goals, particularly those addressing education and environmental sustainability. Her work bridges theoretical perspectives with practical applications in transdisciplinary educational settings. Recent publications explore higher education's adaptation to technological disruptions and the integration of sustainability principles in curricula. She has authored articles in journals like the International Journal of Sustainability in Higher Education and contributed chapters to the International Encyclopedia of the Social & Behavioral Sciences . With an h-index of 2 and over 30 citations, her research emphasizes actionable solutions for transitioning education systems toward sustainability. No specific grants or student advisement roles are detailed in the provided information.
