جست‌وجوی استاد و پژوهشگر

• Wearable Sensors
• Smart Garments
• Sustainable Textiles
• +۵ مورد دیگر

Dr. Shirley Coyle is an Assistant Professor in the School of Electronic Engineering at Dublin City University (DCU) and Programme Chair for the BSc Global Challenges. She holds a BEng in Electronic Engineering from DCU (2000) and a PhD in Biomedical Engineering from NUI Maynooth (2005). Her career includes roles as a Telecoms Engineer at Siemens, Research Fellow at the National Centre for Sensor Research, and Team Leader of Wearable Sensors in the INSIGHT Centre for Data Analytics. She also studied part-time at the Grafton Academy for Fashion Design and later founded a consultancy in wearable technologies. Her research focuses on smart garments, wearable sensors, and sustainable textiles, with applications in healthcare, sports performance, and S.T.E.A.M. integration. Key interests include developing wearable chemical sensors, energy-autonomous sensing systems, and IoT-enabled rehabilitation devices. She has pioneered work on wearable sensors for monitoring chronic diseases, athlete training, and home rehabilitation using VR. Dr. Coyle’s work spans interdisciplinary collaboration, combining biomedical engineering with textile design. Her contributions include innovations in electrospun textiles, self-powered sensors, and sensor integration with microfluidics. She has held leadership roles in DCU’s Governing Authority and promotes STEM education through design-focused initiatives.

• Machine Learning
• Computational Biology
• Bioinformatics
• +۴ مورد دیگر

Catherine Mooney is a Professor in the School of Computer Science at University College Dublin (UCD), leading the Life Science Data Analytics Group (LiSDA). Her research focuses on applying machine learning to healthcare challenges, including biomarker development, clinical decision support systems, and addressing ethical and technical barriers in healthcare AI. Education: BSc in [field unspecified] from Trinity College Dublin PhD in Computer Science from UCD Prof Dip University Teaching & Learning from UCD Research Interests: Machine Learning applications in healthcare Biomarker discovery for neurological and metabolic conditions Explainable AI for clinical decision support Promoting diversity and inclusion in STEM education Her work bridges computational methods with medical challenges, emphasizing ethical AI and translational research. Notable Awards: Best Paper Award in Applied Biosciences (2023) UCD Long-Service Award (2022) Best Poster Award at ITiCSE ’20 (2020) Her research has led to impactful tools like LiSDA’s clinical decision support systems for epilepsy and pregnancy care. She also advocates for gender diversity in computing, serving in leadership roles like Vice Principal for EDI in UCD’s College of Science (2022–2024).

• Artificial Intelligence
• Machine Learning
• Medical Imaging
• +۴ مورد دیگر

Prof Noel O'Connor is a Full Professor at Dublin City University's School of Electronic Engineering, specializing in cutting-edge research at the intersection of artificial intelligence (AI), medical imaging, robotics, and smart city technologies. His work spans applications such as cardiac MRI reconstruction, robotic manipulation using reinforcement learning, and the development of the Smart DCU Digital Twin for autism-friendly university environments. Research interests include AI-driven medical diagnostics, multimodal data fusion, and adaptive systems. His contributions to cardiac MRI reconstruction and transformer-based medical imaging analysis reflect a strong focus on healthcare innovation. He also explores ethical AI practices to reduce social bias in foundation models. Recent work emphasizes smart infrastructure projects, such as optimizing parking recommendations for electric vehicles and enhancing accessibility through digital twin frameworks. His research often integrates real-time sensor data and multi-agent systems to address complex urban challenges. No scientific awards are listed. Collaborations include the ASU-DCU International Research Program on Sensors and Machine Learning. Advising details and grant information are not explicitly provided.

• Neural Engineering
• Neuromuscular Systems
• Electromyography
• +۴ مورد دیگر

Madeleine Lowery is a Professor in the School of Electrical and Electronic Engineering at University College Dublin. She leads the Personal Sensing research group, focusing on engineering approaches to study the human nervous system in health and disease, with applications in therapies for impaired motor function. Her interdisciplinary research integrates neural engineering, electromyography, and biomedical signal processing. Specializes in neuromuscular systems and neural control of movement Develops myoelectric control systems for artificial limbs Designs high-density electrode systems for neural activity recording Investigates deep brain stimulation mechanisms in Parkinson’s disease models Her research spans neurodegenerative disorders (ALS, Huntington’s disease) and rehabilitation technologies , including wearable sensors for gait and sleep analysis. Key methodologies involve computational modeling , adaptive control systems , and biomedical signal analysis .

• AI at the Edge
• Low Power Embedded Systems
• Reliable and Secure Computing
• +۸ مورد دیگر

Emanuel Popovici is a Senior Lecturer in Electrical and Electronic Engineering at University College Cork (UCC), Ireland. He holds a Dipl. Ing. in Computer Engineering from the University Politehnica Timisoara, Romania, and a PhD in Microelectronics from UCC. His research focuses on AI at the edge, low-power embedded systems, and secure computing, with applications in healthcare, energy, and IoT. Notable projects include award-winning work in neonatal EEG monitoring, smart beehive systems, and energy-efficient wireless nodes. He has authored over 250 papers and received prestigious awards like the Qualcomm Faculty Award (2024) and three IEEE/IBM Smarter Planet Challenge titles. Education: Dipl. Ing. in Computer Engineering, University Politehnica Timisoara (Hardware Design focus) PhD in Microelectronics, UCC (National Microelectronics Research Centre) Research interests span AI-driven hardware, secure communications, and interdisciplinary collaborations across engineering, medicine, and environmental science. His work emphasizes practical solutions for real-world challenges, such as energy-efficient sensor networks and medical diagnostic tools. Scientific achievements include over 50 awards, including the Reed and Mallick Medal (2020) for urban planning contributions. His lab pioneered innovations like the neonatal EEG sonification system and blockchain-based IoT security frameworks. Collaborative projects span disciplines like anatomy, medicine, physics, and business. His group's work on ultra-low-power wireless nodes and FPGA-based cryptographic processors highlights their focus on energy efficiency and reliability.

• Rehabilitation Engineering
• Human Motor Control
• Biomechanics
• +۵ مورد دیگر

Giacomo Severini is a Lecturer in Biomedical Engineering at the School of Electrical and Electronic Engineering, University College Dublin. His research focuses on human motor control, motor learning, and rehabilitation robotics, aiming to develop innovative tools for rehabilitating individuals with movement impairments. He holds an MS (2008) and PhD (2012) in Electrical Engineering and Biomedical Engineering from Roma Tre University, Italy, and previously worked as a Research Associate at Spaulding Rehabilitation Hospital (2011–2015) and postdoctoral researcher at Harvard Medical School (2012–2015). Research Interests: Dr. Severini investigates neuromuscular control mechanisms using robotics, computational modeling, and clinical biomechanics. Key areas include: Rehabilitation engineering for stroke, cerebral palsy, and spinal injuries Muscle synergy analysis to decode motor recovery patterns Robot-assisted gait and upper-limb training Neural-inspired controllers for adaptive movement Biomechanical assessments of sit-to-stand, walking, and cycling Publication Trends: His 15 most recent articles (2023–2025) emphasize quantitative rehabilitation science , with recurring themes in muscle synergy applications for clinical diagnostics, robot-assisted therapy efficacy, and predictive simulations of movement. Studies frequently integrate multimodal data (EMG, EEG, kinematics) and target neurological populations (stroke, cerebral palsy). Awards: No scientific awards mentioned in available sources. Affiliations: As a Funded Investigator in the Personal Sensing research group, he collaborates on projects bridging engineering and clinical rehabilitation. No specific labs or student advising details are provided.

• Signal Processing
• Machine Learning
• Computer Engineering
• +۳ مورد دیگر

Ehsan Namjoo serves as a Research Fellow in the Department of Electronics & Computer Engineering at the University of Limerick, with a primary affiliation at Lero – the Irish Software Research Centre. His multidisciplinary work bridges theoretical signal processing, machine learning applications, and hardware implementation for real-world systems. His research spans signal processing (DOA estimation under non-ideal noise conditions, EEG source imaging), machine learning (explainable AI for medical diagnostics, feature selection in cancer detection), and computer engineering (polar code decoders, visible light communication systems). Notable biomedical applications include breast cancer diagnosis and epileptic source analysis, while cybersecurity work focuses on intrusion detection in cloud environments. Recent publications (2021-2025) reveal a consistent trajectory toward developing lightweight, interpretable models for tabular medical data alongside robust signal processing frameworks for communication systems. His work increasingly integrates hardware-aware algorithms, particularly in polar coding implementations, and emphasizes practical validation through experimental demonstrations in visible light networks. As an active Lero researcher, Namjoo participates in Ireland's national software research ecosystem, contributing to interdisciplinary projects that connect theoretical innovations with healthcare, communications, and security applications through collaborative frameworks.

• Machine Learning
• Data Analytics
• Blockchain Technology
• +۷ مورد دیگر

Prof. Tahar Kechadi is a Principal Investigator at the Insight Centre for Data Analytics , specializing in Machine Learning & Statistics and Optimisation & Decision Analytics . His research spans interdisciplinary domains including agriculture, healthcare, and cybersecurity. University : Insight Centre for Data Analytics Role : Principal Investigator Ranks : Professor His current research focuses on applying machine learning to smart agriculture (e.g., crop yield prediction, data engineering), blockchain technologies (e.g., energy trading, e-voting), and privacy-preserving systems in healthcare and cybersecurity. Publications highlight advancements in multi-modal analysis , deep learning architectures , and game-theoretic clustering . Recent work explores data contamination in LLMs , privacy-aware blockchain systems , and distributed reputation management . His team develops tools for agro-climate modeling , medical diagnostics , and cloud forensic readiness . Contact: tahar.kechadi@insight-centre.org

Graham Healyمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Brain-Computer Interfaces
• Eye-Tracking Systems
• +۳ مورد دیگر

Graham Healy is Assistant Professor and COMSCI Programme Board Chair at Dublin City University's School of Computing. His research develops hybrid human-computer interaction systems using bioelectric signals (EEG), eye-tracking, and machine learning. Current projects include the CASTLE multimodal dataset, AMBER BCI dataset for naturalistic settings, and DERCo EEG-reading comprehension corpus. Dr. Healy creates interactive retrieval systems like VEAGLE (eye gaze-assisted video browsing) and LifeInsight (lifelog search engine), winning competitive evaluations at Video Browser Showdown and Lifelog Search Challenge events. His neuroergonomics research investigates pre-stimulus EEG for predicting driver reaction times, while health informatics projects develop machine learning models for early gestational diabetes prediction using electronic health records. With PhD expertise in brain-computer interfaces from DCU, Dr. Healy's work spans experimental neuroscience, information retrieval, and clinical applications. Recent publications address reproducibility challenges in medical AI and validate diagnostic coding in electronic health systems. His NeuroScore framework evaluates GAN performance using neural responses, advancing quality assessment in synthetic media.

• Artificial Neural Networks
• Anomaly Detection
• Machine Learning
• +۴ مورد دیگر

Mehran Hossein Zadeh Bazargani is a Marie Curie Post Doctoral Fellow at the School of Mathematics and Statistics , University College Dublin. His research focuses on brain-inspired artificial neural networks, anomaly detection in medical data, and interpretable machine learning. He has contributed to the MED-I consortium and founded the educational platform MLDawn . Education: PhD in Machine Learning (University College Dublin) Research Interests: Developing artificial neural networks for perceptual learning and decision-making, anomaly detection in time-series (ECG, EEG) and medical images (fMRI, X-ray), and computational neuroscience applications under the Free Energy Principle. Teaching Activities: Founder of MLDawn (2018–Present), lecturer at Queens University Belfast (2020), teaching assistant at UCD (2017–2020), and instructor in Iran (2013–2015). Scientific Contributions: 8 publications across anomaly detection, medical image analysis, and molecular communication. Key works include the D-RBFDD network and de-identification frameworks for medical data. Emails: mehran.hosseinzadehbazargani@ucd.ie, mldawn2018@gmail.com

David McGovernمشاهده پروفایل

استادیار

• Sensory Neuroscience
• Perceptual Decision Making
• Multisensory Integration
• +۳ مورد دیگر

Dr. David McGovern is an Assistant Professor at the School of Psychology, Dublin City University , specializing in sensory neuroscience and perceptual decision-making. He earned his PhD in Visual Neuroscience from the University of Nottingham and holds prior degrees in Cognitive Science from University College Dublin. Teaching: Modules in Cognition, Perception, and Behavioural Neuroscience Methods across four programs (BSc/MSc Psychology, Psychology & Mathematics, Psychology & Disruptive Technologies). Research: Investigates multisensory integration, aging effects on perceptual decision-making, and computational modeling. Uses psychophysics, EEG, and simulations. Selected Article Trends: Focus on sensory adaptation, age-related neural changes, multisensory dynamics, and computational approaches to cognition. Recent work links perceptual training to improved temporal integration and explores decision-making in sports and AI. Honors: Government of Ireland Postdoctoral Fellowship (2013) Brain Travel Scholarship (2011) Universitas 21 Scholarship (2009) University of Nottingham Research Scholarship (2006) Projects: Principal Investigator for Evaluating the Role of Sensory Perception in Elite Soccer (2024–2028) and Neurally-Informed Modeling of Adult ADHD (2022–2026).

• Biomedical Signal Processing
• Renewable Energy
• Wind and Wave Power
• +۴ مورد دیگر

Gordon Lightbody is a Senior Lecturer in the Department of Electrical Engineering at University College Cork (UCC). He holds a MEng (Distinction) and PhD from Queen's University Belfast. His research focuses on intelligent control systems applied to biomedical engineering, renewable energy, and power systems. He has been a key figure in projects like the MAREI and INFANT research centres, addressing marine energy and neonatal health challenges. His academic career includes roles at Queen's University Belfast (1993-1997) and UCC since 1997, where he was promoted to Senior Lecturer in 2008. He has contributed to over 194 peer-reviewed publications and won the UCC Invention of the Year Award (2010) for neonatal seizure detection algorithms. Research interests span energy systems (wind/wave power, smart grids) and biomedical signal processing (neonatal EEG analysis). His work on neonatal seizure detection is under clinical trials and recognized in government innovation reports. He also serves on committees like the IFAC National Member Organisation for Ireland. He has supervised 17 PhD students and currently leads a research group with 5 PhD candidates. His grants include SFI funding for NEOPRISM and roles in MAREI (€28M) and INFANT (€6M) centres.

Ciaran MacNameeمشاهده پروفایل

دانشیار

• Embedded Systems
• Real-time Systems
• Test Engineering
• +۴ مورد دیگر

Ciaran MacNamee serves as Associate Professor in the Department of Electronic and Computer Engineering within the Faculty of Science and Engineering at the University of Limerick, Ireland. His office is located in ER2-020 with primary contact via ciaran.macnamee@ul.ie. With 15 years of academic experience following 16 years in industry, he maintains active research and teaching roles in embedded systems and hardware design. His educational background includes: PhD (awarded 2008) M.Eng (awarded 1996) Graduate Diploma BE from University College Dublin (awarded 1978) MacNamee's research centers on embedded systems development with specialized expertise in real-time system verification, debugging methodologies, and test engineering. His work extends to System-on-Chip testing, low-power scan techniques, and hardware implementations for biomedical applications. Recent projects demonstrate significant crossover into Internet of Things applications for environmental monitoring and smart infrastructure, reflecting his adaptability to emerging technological domains while maintaining core hardware focus. His publication trends since 2016 reveal strategic expansion from traditional embedded systems into applied IoT solutions, with notable contributions in automotive safety verification (2016), environmental monitoring systems (2018), and biomedical hardware implementation (2021). This evolution demonstrates consistent application of core verification and testing expertise across diverse implementation domains while maintaining strong industry relevance. Professional recognition includes: Winter Award for Excellence in Teaching (2014) With extensive industrial background including senior design engineering roles at Ashling Microsystems, MacNamee bridges academic research with practical implementation. His grant-funded projects focus on real-time system verification, low-power testing methodologies, and IoT applications, often involving cross-departmental collaboration. Current advising activities emphasize embedded systems design and hardware verification principles. He contributes to the University of Limerick's research ecosystem through the Department of Electronic and Computer Engineering's embedded systems group, collaborating with computer science researchers and industry partners on hardware-software co-design projects. His work with the IEEE and interdisciplinary teams supports ongoing development of safety-critical system verification frameworks.

Maria Chiara Levaمشاهده پروفایل

مدرس ارشد

• Human Factors
• Human Reliability Analysis
• Human Machine Interface Design
• +۲ مورد دیگر

Dr Maria Chiara Leva serves as a Senior Lecturer within the Faculty of Sciences and Health at Technological University Dublin (TU Dublin), specifically in the Department of Food Science & Environmental Health. She concurrently holds a visiting lecturer position for Risk Assessment and Safety Management in Trinity College Dublin's School of Engineering, while maintaining associated Principal Investigator roles at TU Dublin's Science and Technology in Advanced Manufacturing research centre and Trinity's Centre for Innovative Human Systems. Her research program centers on Human Factors, Human Reliability Analysis, Human Machine Interface Design, Safety Management Systems, and Safety Culture, with over 60 publications spanning operational risk assessment and safety engineering applications. Dr Leva's work demonstrates consistent evolution from foundational human reliability modeling toward integrated safety management frameworks, with recent publications emphasizing real-time workload monitoring, risk intelligence systems, and cross-industry applications in manufacturing and process safety. Her research bridges theoretical human factors principles with practical implementation in high-risk operational environments. Dr Leva leads significant industry-academic initiatives including the spin-out company 'Tosca Human Factors Solutions', which originated from an EU project she directed as Principal Investigator. Her leadership extends to professional societies where she co-chairs the European Safety and Reliability Association's Human Factors technical committee and previously chaired the Irish Ergonomics Society. She also co-founded the annual Symposium on Human Mental Workload, now in its third iteration. Scientific Awards Female Founder Competitive Start Fund (National Digital Research Centre and Enterprise Ireland, 2016) Dr Leva has secured substantial research funding through EU projects and national grants, establishing her campus company as a conduit for translating academic research into industry solutions. Her advisory role in Tosca Human Factors Solutions demonstrates successful commercialization of academic expertise, while her ongoing research collaborations with manufacturing and process safety sectors highlight practical impact. She actively mentors through her academic positions and symposium organization, fostering next-generation researchers in human factors engineering. Her work operates within the interdisciplinary ecosystem of TU Dublin's Food Science & Environmental Health department and Trinity's engineering research centres, focusing on human-system integration challenges across food safety, industrial manufacturing, and critical infrastructure sectors.

• Biomedical Signal Processing
• Machine Learning
• Neonatal EEG Analysis
• +۵ مورد دیگر

William Marnane is a Professor of Electrical and Electronic Engineering at University College Cork (UCC). He holds a B.E. from UCC (1984) and a D.Phil. from the University of Oxford (1989). His career includes roles as Lecturer (1989), Senior Lecturer (1999), Dean of Graduate Studies (2013–2016), and Head of the School of Engineering (2016–2019). He has led major research initiatives, including the SFI-funded INFANT Centre and the Claude Shannon Institute. His research focuses on biomedical signal processing, machine learning, and neonatal EEG analysis, with notable contributions to neonatal seizure detection algorithms and fetal health monitoring. He has been awarded the Giner de Los Ríos Visiting Research Fellowship (2007, 2020) and leads projects funded by Wellcome Trust, Science Foundation Ireland, and EU grants. His educational background includes significant contributions to curriculum development and graduate training in engineering and biomedical sciences. He has supervised numerous research projects, including advancements in cryptographic hardware, embedded systems, and low-power signal processing architectures. Research highlights include the ANSeR neonatal seizure detection algorithm (Wellcome Trust-funded), clinical trials on EEG-based seizure recognition, and development of secure TLS coprocessors. He has published over 200 peer-reviewed articles, with key contributions in neonatal EEG analysis, machine learning applications in healthcare, and cryptographic processor design. Current research explores AI for fetal heart rate monitoring and wearable health technologies. Grants and partnerships include leadership roles in EU-funded projects, SFI Strategic Research Clusters, and industry collaborations. He co-directs the INFANT Centre, bridging engineering, medicine, and data science for translational research in neonatal care.