جست‌وجوی استاد و پژوهشگر

John Nelsonمشاهده پروفایل

استاد

• Biomedical Engineering
• Activity Recognition
• Wireless Sensor Networks
• +۵ مورد دیگر

John Nelson is a Professor at the University of Limerick's Department of Electronic and Computer Engineering, part of the Faculty of Science and Engineering. His contact information includes email john.nelson@ul.ie and phone +353-(0)61-202358, with office location D2-025. His primary research interests focus on biomedical applications of engineering principles, particularly in: Medical device development including pulse oximetry and therapeutic technologies Activity recognition systems using wearable sensors and accelerometers Wireless body area networks for health monitoring AI applications in healthcare and public systems Fall detection and mobility monitoring for assisted living Mobile health frameworks for psychological interventions Analysis of his 15 most recent publications (2014-2021) reveals three dominant themes: Medical sensing technologies for pulse oximetry, aneurysm monitoring and ultrasound imaging AI/Deep Learning applications ranging from public space analysis to ethical enforcement systems Comprehensive activity recognition frameworks using multi-sensor fusion The research consistently demonstrates interdisciplinary collaboration across medicine, computer science and psychology. No awards, students, or lab/team information is available in the provided materials.

• Simulation and Control of Manufacturing Systems
• Digital Manufacturing Applications
• Industry 4.0 Technologies
• +۳ مورد دیگر

Nikolaos Papakostas is an Associate Professor at the School of Mechanical and Materials Engineering, University College Dublin (UCD), and Director of the Master of Engineering with Business Programme. His expertise spans simulation, control, and scheduling of manufacturing systems, digital manufacturing, Industry 4.0 technologies, and IoT applications in supply chains. He holds a PhD in Engineering (2000) and a Diploma in Mechanical Engineering (1995) from the University of Patras, Greece. Prior to UCD, he worked at the Laboratory for Manufacturing Systems and Automation (LMS) and served as CIO at INTRAMET Steel. He has led numerous European projects and collaborated with industries in automotive, aerospace, and biotechnology. Research: Focuses on additive manufacturing, robotics, and digital twins. Recent work includes porosity prediction in AM, human-robot collaboration in bioprocessing, and blockchain for product development. He has over 80 peer-reviewed publications and 500+ citations. Key grants include the SHERLOCK project (EU-funded) on collaborative workplaces and I-Form, an Advanced Manufacturing Research Centre. Teaching: Coordinates modules like Applied Robotics Research, Robotic Applications, and Operations Management. His teaching emphasizes integrating business and engineering through project-based learning. Affiliations: Member of CIRP, IEEE, and the Technical Chamber of Greece. His work bridges academia and industry, addressing challenges in flexible manufacturing, sustainability, and smart technologies.

• Structural Health Monitoring (SHM)
• Earthquake Engineering
• Smartphone Sensor Technologies
• +۵ مورد دیگر

Dr. Ekin Ozer is an Assistant Professor at University College Dublin's School of Civil Engineering. His research focuses on vibration-based structural health monitoring (SHM), earthquake engineering, and mobile sensor technologies. He holds a PhD from Columbia University (2016) and has prior experience in academia (Middle East Technical University) and industry (Novum Structures). His work emphasizes smartphone and participatory sensing for bridge and building monitoring, with contributions to Bayesian risk assessment and machine learning applications. Education: BSc/MSc in Civil Engineering from Bogazici University, MPhil/PhD from Columbia University. Grants include the FLAME project (UCD SATLE) for 3D learning tools and transnational university initiatives. Key research trends in his articles include smartphone-driven SHM innovations, seismic risk assessment frameworks, and integration of cyber-physical systems for infrastructure resilience. He actively supervises PhD students and teaches modules like Structural Analysis, Bridge Engineering, and Case Studies in Infrastructure Design.

James Garlandمشاهده پروفایل

مدرس

• Machine Learning
• Embedded Systems
• FPGA/ASIC Design
• +۴ مورد دیگر

Dr. James Garland is a Lecturer in the Department of Electronic Engineering and Communications at South-East Technological University (SETU), part of the engCORE academic unit. He holds a PhD in Computer Science from Trinity College Dublin (2022). His research focuses on micro-architectural implementations of deep learning algorithms in FPGA/ASIC/embedded systems, with applications in robotics and aerospace engineering. Key areas include defect detection via unmanned aircraft systems, image classification, and GAN-based enhancement for license plate recognition. Education: PhD in Computer Science (Trinity College Dublin, 2022). Research interests span machine learning optimization, embedded systems design, and aerospace robotics. His work emphasizes low-complexity hardware solutions for high-performance computing and energy efficiency. Recent articles explore topics like super-resolution GANs, zero-shot learning in pre-trained models, and spatial mapping for aircraft defect localization. He actively contributes to peer-reviewed journals, including Journal of Universal Computer Science and IEEE Access . Media coverage includes collaborations with the Irish Department of Aerospace and Mechanical Engineering. Teaching responsibilities include courses on artificial intelligence, control systems, and avionics fundamentals.

Oisin Cawleyمشاهده پروفایل

مدرس

• Software Engineering
• Artificial Intelligence
• Medical Device Software Development
• +۳ مورد دیگر

Dr Oisin Cawley is a Lecturer in the Department of Computing at South East Technological University. His work spans software engineering methodologies, artificial intelligence applications, and educational technology innovation. He holds a PhD in Software Engineering from the University of Limerick (2009), an MBA from Dublin City University, and a BSc in Computer Science from University College Dublin. Education Background: BSc (Hons) Computer Science, University College Dublin MBA, Dublin City University PhD in Software Engineering, University of Limerick Research focuses on regulatory impacts on software development, particularly in medical devices, and applies agile/lean methods to regulated environments. Recent work explores AI applications in gaming, academic writing support tools, and healthcare technology education. He has collaborated internationally across Ireland, Sweden, and the Netherlands. Professional Experience: Lecturer, South East Technological University (current) Lecturer, Institute of Technology Tallaght Research Assistant, Lero-The Irish Software Research Centre Labs/Teams: Part of compuCORE, a research cluster focused on computing innovation. Collaborates with industry partners on healthcare technology projects and educational AI solutions.

• Energy Efficient Networking
• Hardware Acceleration
• Cryptography Algorithms
• +۴ مورد دیگر

Dr. Xiaojun Wang is an Associate Professor at the School of Electronic Engineering, Dublin City University (DCU). He holds a BEng and MEng from Beijing University of Posts and Telecommunications (BUPT) and a PhD from Staffordshire University (UK). His research focuses on energy-efficient networking, hardware acceleration for packet classification/deep inspection, and cryptography algorithms. He has been instrumental in establishing China-Ireland academic collaborations, including the China-Ireland International Conference on Information and Communications Technologies (CIICT), and coordinated a successful joint Telecommunications Engineering program with Wuhan University (2006–2012). He is also a member of DCU's Entwine Research Centre. Key roles include Head of China Affairs at DCU (2002–2007), contributing to institutional partnerships. His technical work spans green energy solutions for networks, quantum computing protocols, and hardware-software co-design for cryptographic systems. He has led projects on edge computing security, vehicular communication optimization, and blockchain-based trust frameworks. Educations: BEng in Computer & Communications, BUPT (1984) MEng in Computer Applications, BUPT (1987) PhD in Engineering, Staffordshire University (1992) Affiliations: Member of Entwine Research Centre Former Head of China Affairs, DCU His recent publications emphasize secure edge computing, quantum steganography, and 5G resource orchestration. He has pioneered energy-efficient router architectures and contributed to standards for vehicular networks and blockchain trust systems.

• Signal Processing
• Video Processing
• Bayesian Inference
• +۵ مورد دیگر

Professor Anil Kokaram is a distinguished academic and researcher in Electronic Engineering at Trinity College Dublin (TCD), Ireland. He holds a PhD in Signal Processing from the University of Cambridge (1993). As a Fellow of Engineers Ireland and recipient of an Academy Award (Oscar) for his work in video processing, he is renowned for contributions to digital video restoration, multimedia forensics, and video compression. From 2011–2017, he led the Media Algorithms Team at YouTube/Google, advancing cloud-based video transcoding and enhancement technologies. His research bridges academia and industry, with innovations in Bayesian inference, motion estimation, and neural network applications for video processing. **Education**: PhD in Signal Processing, University of Cambridge (1993). **Key Roles**: Former Associate Editor of IEEE Transactions on Video Technology and Image Processing. Founded GreenParrotPictures (acquired by Google), producing video enhancement software. **Research Focus**: Video compression artifacts, perceptual quality metrics (e.g., ViSQOL), and adaptive streaming algorithms. **Notable Projects**: Developed frameworks for automated sports broadcasting, noise reduction in medical imaging, and synchronization of user-generated videos. **Awards**: 2007 Science & Engineering Academy Award (Oscar), 2007 Fellow of Engineers Ireland. **Labs/Teams**: Leads the Signal Media Algorithms group at TCD, collaborating with industry partners like Google on large-scale video analysis systems. His work emphasizes practical applications of signal processing in creative industries, including film post-production and virtual production.

Michael Reichertمشاهده پروفایل

دانشیار

• Animal Communication
• Behavioral Ecology
• Evolutionary Biology
• +۳ مورد دیگر

Dr. Michael Reichert is an Associate Professor in the Department of Integrative Biology at Oklahoma State University (OSU), where he has served since January 2019, transitioning from Assistant to Associate Professor in July 2024. Previously, he was a Senior Postdoctoral Researcher at University College Cork (UCC), working under Prof. John Quinn on the evolutionary ecology of cognition in wild great tits. Reichert holds a BSc in Biology from the University of North Carolina and a PhD in Biological Sciences from the University of Missouri (2011). He conducted postdoctoral research at the University of Wisconsin-Milwaukee and Humboldt University in Berlin before joining UCC. His academic career includes certifications such as a Postgraduate Certificate in Teaching and Learning in Higher Education from UCC. His research focuses on animal communication and cognition, particularly in frogs and insects, exploring how environmental factors influence behavioral plasticity, sexual selection, and learning. Key areas include acoustic signaling strategies, female mate preference dynamics, and cognitive mechanisms in contests. He leads the Reichert Lab, which investigates bioacoustics, behavioral ecology, and evolutionary processes using interdisciplinary approaches. Reichert collaborates on educational outreach, such as developing free high school lessons on tradeoffs in animal behavior with the Galactic Polymath Education Studio. His work emphasizes broader impacts, including NSF-funded initiatives like the ON-RaMP program for post-baccalaureate researchers. He also engages in interdisciplinary projects, such as analyzing gut microbiota effects on avian behavior and cognition. His lab’s current projects include studying cognition in contests, the effects of noise on signal preferences, and the role of perception in communication networks. Reichert’s contributions span peer-reviewed publications, seminar series (e.g., Braincoustics), and mentorship in organismal biology and ecology.

Harry Nguyenمشاهده پروفایل

مدرس

• Reliable AI
• Multimodal Machine Learning
• Health Informatics

Harry Nguyen (Hoang D. Nguyen) is a Lecturer and Programme Director for the MSc in Computing Science at University College Cork. Affiliated with the SFI Research Centre for Data Analytics, he leads research in reliable AI systems for healthcare and sustainability. Research Focus: Develops robust ML models integrating graph networks and multimodal learning, with applications in medical diagnosis (e.g., COVID-19 detection via cough analysis) and environmental monitoring. Directs the Reliable Machine Intelligence research group. Advising: Mentors 15+ graduate students on projects spanning federated learning, sound-based diagnostics, and conversational AI for diabetes care. Secured funding from Science Foundation Ireland for CRT-AI initiatives.

Kashif Naseer Qureshiمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Healthcare Systems
• +۶ مورد دیگر

Kashif Naseer Qureshi is an Associate Professor in the Department of Electronic and Computer Engineering at the Faculty of Science and Engineering, University of Limerick, Ireland. His research focuses on the intersection of artificial intelligence, healthcare systems, blockchain technology, and wireless communication networks. His recent work explores: AI-driven healthcare architectures (tri-tier models, distributed networks) Blockchain applications in medical and smart city systems Advanced machine learning techniques for data imbalance problems Edge computing security and privacy frameworks Next-generation AI language models with ethical considerations Publications demonstrate a strong emphasis on practical implementations across IoT, cybersecurity, and smart infrastructure domains. His email contact is KashifNaseer.Qureshi@ul.ie .

Jennifer Hyndmanمشاهده پروفایل

مدرس

• Data Analytics
• STEM
• Technology Enhanced Learning
• +۳ مورد دیگر

Jennifer Hyndman is a Lecturer in the Department of Computing at Atlantic Technological University, Ireland. Her work bridges academic teaching and cutting-edge research, with a focus on integrating technology into education and advancing computational methodologies. Education : PhD in Computing (2008), supervised by Dr. Tom Lunney and Prof. Paul Mc Kevitt at the University of Ulster, Magee, Derry. Research Interests Jennifer's research spans Data Analytics , STEM , Technology Enhanced Learning , and IoT . Her work explores applications of Artificial Intelligence and Machine Learning in educational contexts, robotics, and ambient intelligent systems. Publication Trends Her publications (2008–2024) demonstrate a trajectory from foundational work in ambient learning environments for children to advanced studies in swarm robotics and deep learning applications. Recent contributions focus on tertiary education pedagogy, cloud computing , and autonomous systems . Teaching Contributions She has taught diverse subjects including Mathematics for Computing , Python Scripting , Data Analytics , and Legal, Ethical, and Social Issues in Computing .

• Industry 4.0
• Computer Vision
• Robotics Safety
• +۳ مورد دیگر

Jacqueline Humphries is a Lecturer in the Department of Information Technology at the Faculty of Applied Sciences and Technology. Her research focuses on Industry 4.0, robotics safety, computer vision, and quality management systems. She has contributed to over 10 peer-reviewed publications between 2019-2024, with a particular emphasis on human-robot collaboration safety, manufacturing error reduction, and sustainable production frameworks. Key research themes include optimizing human-robot interaction through computer vision fusion, enhancing quality 4.0 standards, and designing effective industry-academia partnerships for technology adoption. Her work aligns with UN Sustainable Development Goals related to sustainable industry and innovation. Recent studies explore topics like protective separation distance in collaborative robotics, lighting conditions' impact on object detection accuracy, and taxonomy development for human augmentation technologies in manufacturing. No formal awards are listed, though her h-index of 20 reflects significant citation activity.

• Material Science
• Robotics
• Computer Vision
• +۳ مورد دیگر

Dr. Sean Lyons is a Lecturer at the Faculty of Science and Health, Department of Bioveterinary and Microbial Sciences. With an h-index of 24 and over 2072 citations, his research spans Material Science, Robotics, and Sustainable Manufacturing. His work focuses on advanced manufacturing technologies, including Asset Administration Shells , OPC UA protocols , and ROS-based computer vision systems , particularly for robotics and polymer-metal composites. He has contributed to optimizing electroless plating techniques for ionic polymer-metal composites (IPMCs) and sustainable production systems. Recent publications in 2024 highlight his expertise in Smart Manufacturing , Computer Vision , and Polymer Engineering . His research aligns with the United Nations Sustainable Development Goals (SDGs) through innovations in sustainable materials and automation. Lyons has collaborated on interdisciplinary projects, including with Dr. Costelha, Dr. Devine, and Professor Higginbotham, across institutions in Europe. His 70+ research outputs since 2006 reflect sustained contributions to manufacturing and materials science.

Martin Hayesمشاهده پروفایل

استاد

• Systems Science
• Computer based Control
• Machine Learning
• +۱۱ مورد دیگر

Martin Hayes is a Professor in the Department of Electronics & Computer Engineering at the University of Limerick and a Professor at Lero – the Irish Software Research Centre. He currently serves as Academic lead for the HCI UL@Work project and previously held the Head of Department position from 2017 to 2021, with continuous faculty service since 1995. Education: PhD in Engineering from Dublin City University (1997) M.Eng (1992) B.Eng (1989) His research expertise spans Systems Science, Computer based Control, Machine Learning, and Artificial Intelligence, with significant contributions to Smart Manufacturing, Wireless Networks, and Robust Control. He integrates advanced control theory with AI methodologies to address challenges in manufacturing optimization, power management, and biomedical systems, emphasizing practical industrial applications and system reliability. Recent publications (2024-2025) demonstrate a concentrated focus on AI-driven industrial solutions, particularly deep learning for defect detection in remanufacturing, real-time failure prediction in additive manufacturing, and secure IoT access control systems. These works highlight his commitment to enhancing manufacturing efficiency through computational innovation and robust security frameworks. Scientific Awards: Community Service Award UL (1999) Visiting Research Fellow, University of Leicester (1999) As a core member of Lero, Hayes leads national software research initiatives including the HCI UL@Work project, developing human-centered computing solutions for workplace environments. His research directly supports UN Sustainable Development Goal 9 (Industry, Innovation and Infrastructure) through advancements in smart manufacturing and resilient systems engineering.

John Dooleyمشاهده پروفایل

استادیار

• Digital Signal Processing
• Spectrally Efficient Modulation Schemes
• High-Frequency Circuits
• +۳ مورد دیگر

John Dooley is an Assistant Professor in the Department of Electronic Engineering at Maynooth University , Ireland. He also serves as the Programme Director for the BE/ME Electronic Engineering program. He is a Principal Investigator on the ORCHESTRA-6G project, funded by Science Foundation Ireland (SFI), and a Funded Investigator in the SFI CONNECT Centre for Telecommunications and the SFI ADVANCE Centre for Research Training . Education: Ph.D. in Electronic Engineering, University College Dublin, 2008 Research Focus: Dr. Dooley’s research spans digital signal processing , spectrally efficient modulation schemes , and applications to high-frequency circuits . His work has significantly impacted power efficiency optimization in wireless communication devices and networks, particularly in digital compensation techniques for mmWave terrestrial and satellite systems . His recent focus includes 6G wireless technologies and next-generation modulation techniques . Publications Trends: His research output reflects a strong emphasis on nonlinear system modeling , power amplifier linearization , and digital predistortion techniques . The articles span from RF circuit design to system-level optimization in wireless communications, with a clear trajectory toward 5G and 6G applications . Grants & Affiliations: Principal Investigator, ORCHESTRA-6G , SFI Frontiers for the Future Grant Funded Investigator, SFI CONNECT Centre for Telecommunications Funded Investigator, SFI ADVANCE Centre for Research Training Labs & Teams: Dr. Dooley is affiliated with the Hamilton Institute at Maynooth University, a multidisciplinary research institute focused on applied mathematics and communications systems. His work also intersects with the Radiospace research group, which explores advanced wireless technologies.