Find Academic Supervisors

• Machine Learning
• Signal Processing
• Speech Processing
• +3 more

Dr. Andrew Hines is a Researcher at the School of Computer Science, University College Dublin, specializing in machine learning applications for signal processing in speech, audio, and video domains. His work focuses on Quality of Experience (QoE) modeling, speech quality assessment, and immersive media analysis. He has held leadership roles in European COST Actions like Qualinet and CryptoAction, and previously worked in industry as a Director of Engineering. University: University College Dublin Role: Director of Research, Innovation and Impact Key Collaborations: IEEE (Senior Member), Audio Engineering Society (Ireland) Research interests center on machine learning for QoE optimization, audio-visual integration, and healthcare applications like heart sound classification and stroke rehabilitation. His recent publications explore self-supervised learning, neural speech codecs, and contextual factors in speech/audio quality assessment. Scientific contributions include awards like IEEE Senior Membership, and his work spans both academic research and industrial engineering in finance and aviation sectors. He leads the QxLab research team at UCD and develops open-source platforms such as WARP-Q and AQP for quality metrics.

• Machine Learning
• Medical Imaging
• Health Informatics
• +3 more

Aonghus Lawlor is an Assistant Professor/Lecturer in Computer Science at the School of Computer Science, University College Dublin. His roles include coordinating modules such as Software Engineering, Data Structures, Machine Learning, and Final Year Project Foundations. He holds an Orcid identifier: 0000-0002-6160-4639. His research focuses on machine learning applications in medical imaging (e.g., MRI, CT), sports science, and healthcare systems. Notable areas include AI-driven diagnostics, cybersecurity in radiology, and genomics for agricultural optimization. Recent work explores ChatGPT4-vision in MS progression, knee osteoarthritis grading via anomaly detection, and reinforcement learning in exercise prescriptions. Professional activities include committee roles in ACM Recommender Systems and Intelligent User Interfaces, grant assessments, and peer reviewing. He has published 137+ outputs, emphasizing interdisciplinary AI solutions with clinical and agricultural impact. Teaching responsibilities span foundational CS courses to advanced ML and project modules. No formal awards are listed, but his work demonstrates contributions to AI ethics, health informatics, and agricultural genomics.

• Semantic Web
• Data Analytics
• Artificial Intelligence
• +3 more

John Breslin is a Personal Professor in Electronic Engineering at the College of Science and Engineering, University of Galway, serving as Director of the TechInnovate and AgInnovate programmes. Associated with two Taighde Éireann – Research Ireland Centres, he is a Principal Investigator at Insight Centre for Data Analytics (specializing in data analytics) and a Funded Investigator at VistaMilk (Agri-Technology), while also leading the EDIH Data2Sustain project. With an h-index of 50, over 12,000 citations, and 300+ peer-reviewed publications including seminal books on the Social Semantic Web, he ranks among Ireland's most influential researchers in digital technologies. Breslin's research fundamentally bridges Semantic Web technologies, AI-driven data analytics, and practical innovation. His co-creation of the SIOC framework—implemented across 65,000+ websites by entities like Yahoo and Boeing—demonstrates real-world impact in social data interoperability. Current work leverages blockchain and federated learning for sustainable Agri-Technology through VistaMilk, while his TechInnovate programmes translate academic research into commercial ventures across healthcare, smart manufacturing, and energy systems. Analysis of his 15 most recent publications reveals dominant themes in AI-enhanced security (35% of works), blockchain applications for sustainability (27%), and multimodal AI for healthcare (20%). His team pioneers privacy-preserving techniques for IoT and medical devices, neurosymbolic visual reasoning frameworks, and federated learning architectures addressing data heterogeneity—directly supporting his roles in national research infrastructures like Insight and VistaMilk. John has received several prestigious awards: IIA Net Visionary Award (twice) ITAG Outstanding Contribution to the ICT Sector Award Galway Chamber President’s Award Best Irish-Published Book Award (2020 for Old Ireland in Colour) Multiple Best Paper Awards He leads major research initiatives funded by Taighde Éireann – Research Ireland: Insight Centre for Data Analytics (as Principal Investigator) VistaMilk SFI Research Centre (as Funded Investigator) EDIH Data2Sustain (as Principal Investigator) His entrepreneurial programs TechInnovate and AgInnovate have mentored 200+ startups, securing €50M+ in follow-on funding. Breslin co-founded PorterShed (Galway City Innovation District) and serves on Scale Ireland's Steering Group, creating Ireland's most active regional innovation ecosystem outside Dublin. He maintains active industry partnerships with Vodafone, Boeing, and agricultural cooperatives through VistaMilk's testbed facilities.

• Machine Learning
• Time Series Analysis
• Text Mining
• +7 more

Dr. Georgiana Ifrim is an Associate Professor at the School of Computer Science, University College Dublin , where she serves as Director of Graduate Research and Co-Lead of the SFI Centre for Research Training in Machine Learning (ML-Labs). She holds concurrent appointments as an SFI Funded Investigator at the Insight Centre for Data Analytics and VistaMilk SFI Research Centre . Her academic journey includes postdoctoral research at Insight Centre, Cork Constraint Computation Centre (4C), and Aarhus University's Bioinformatics Research Centre (BiRC). Education: BSc in Computer Science, University of Bucharest, Romania MSc and PhD in Informatics, Max-Planck Institute for Informatics, Germany Dr. Ifrim specializes in scalable predictive modeling for diverse applications including: Sequence learning (DNA analysis, time series) Real-time prediction for streaming data (news/social media, energy) Interpretable machine learning models Knowledge graph exploitation (WordNet/Yago, Naga) Wearable sensor data analysis (sports science, health monitoring) Energy price forecasting for sustainable systems Her recent publications focus on time series explainability (TSHAP, tsCaptum), multivariate analysis (scalable channel selection), and healthcare applications (fall detection, walking speed estimation). Key contributions include open-source tools like SEQL (sequence learner) and Twitter-Topics (event detection). Scientific Awards: Winner of SNOW@WWW14 Data Challenge As Director of Graduate Research, she oversees advanced academic training while leading funded projects at the intersection of machine learning , real-time analytics , and domain-specific applications in agriculture, healthcare, and digital journalism. Her research group maintains active GitHub repositories with open-source implementations.

• Artificial Intelligence
• Machine Learning
• Medical Imaging
• +4 more

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.

Muhammad Intizar AliView profile

Assistant Professor

• Data Analytics
• Internet of Things (IoT)
• Machine Learning & AI for IoT
• +8 more

Dr. Muhammad Intizar Ali is an Assistant Professor in the School of Electronic Engineering at Dublin City University (DCU). He holds a PhD (with distinction) from Vienna University of Technology, Austria (2011) and has held roles including Adjunct Lecturer and Research Fellow at the Insight Centre for Data Analytics, NUI Galway. His primary research focuses on IoT, Data Analytics, Machine Learning, and Knowledge Graphs with applications in Smart Cities, Manufacturing, Farming, and Healthcare. Education: PhD in Computer Science, Vienna University of Technology (2007-2011) Research Interests: IoT and Edge Analytics Federated and Distributed Machine Learning Semantic Web and Knowledge Graphs Smart Manufacturing and Industry 4.0 Stream Processing and Real-Time Systems Recent Work Trends: His publications emphasize federated learning frameworks, IoT-enabled adaptive intelligence, and knowledge graph applications in industrial contexts. Recent projects include digital twin systems for predictive maintenance and ontology-driven manufacturing solutions. Grants & Projects: Lead Investigator in SFI-funded projects like MultiRoof (2025-2029) and Neuro-Symbolic AI for Building Management EU/Industry collaborations including Terrain-AI and Bentley-funded initiatives Labs & Teams: Active in DCU's Data Analysis and Machine Learning research groups, leading projects like Smart DCU Digital Twin for campus optimization.

Ellen RusheView profile

Assistant Professor

• Deep Learning
• Sign Language Recognition
• Domain Adaptation
• +3 more

Dr. Ellen Rushe is an Assistant Professor at Dublin City University's School of Computing specializing in deep learning with limited supervision. Her research develops solutions for audio-visual data challenges including sign language recognition (SignOn Project), novelty detection, and domain adaptation for sports analytics. Previously a Research Fellow at Trinity College Dublin and Postdoctoral Fellow at UCD, she holds an MSc in Computer Science from UCD and BA in Music Technology from Maynooth University. Research focuses on: Limited-label learning paradigms Sign language recognition for low-resource languages Domain adaptation in sports video analysis Novelty detection in data streams

• Corpus Linguistics
• Terminology
• Discourse Analysis
• +11 more

Dr. Sandrine Peraldi is an Assistant Professor in Linguistics at the School of Languages, Cultures and Linguistics, University College Dublin (UCD). She currently serves as Head of Linguistics and Deputy Head of School, and coordinates the Graduate Diploma in Localisation. With a PhD from Paris Diderot University, her career includes over a decade as Research Director at ISIT in Paris, where she led interdisciplinary research and international collaborations. Her educational background includes: PhD in Theoretical, Descriptive and Automatic Linguistics, Paris Diderot University MLitt, Paris Diderot University Master’s in Language Industry and Specialised Translation Certification in University Teaching and Learning, UCD Dr. Peraldi's research focuses on Corpus Linguistics, Terminology, Discourse Analysis (especially in professional contexts), Intercultural Communication , and Translation Studies , with a strong emphasis on machine translation and post-editing. Her work bridges cognitive, technological, and professional dimensions of language use. Her recent publications reveal a clear trajectory toward the multimodal analysis of virtual workplace communication, particularly how engagement and non-verbal cues function in online meetings. She has also contributed significantly to metaphor analysis in political discourse and the integration of corpus tools in translation workflows. Her scientific contributions are recognized through active participation in peer review for journals such as Meta , TEANGA , and International Journal of Organisations , and editorial leadership as former Editor-in-Chief of the Bulletin du CRATIL . She has secured major funding from the European Commission (TransCert, QUALETRA, PICT, AGORA), UKRI-AHRC, and the National Forum for Teaching and Learning. She supervises PhD students and leads research projects such as the Interactional Variation Online project. She is also involved in professional service through the Human Research Ethics Committee and the EMT assessor network. Dr. Peraldi leads several research and teaching initiatives, including the ENEOLI Cost Action on lexical innovation and the development of scenario-based intercultural learning resources.

Nan ZhangView profile

Research Fellow

• Precision Manufacturing
• Microfluidics
• Nanotechnology
• +3 more

Dr. Nan Zhang is a research leader at the UCD School of Mechanical and Materials Engineering , focusing on precision manufacturing technologies for micro/nano-scale devices. His work bridges lab-scale prototyping and industrial mass production, with applications in medical devices, microfluidics, and functional surfaces. Research Keywords : Precision Manufacturing, Microfluidics, Nanotechnology, Materials Science, Medical Devices, Advanced Manufacturing Research Trends : Recent publications highlight advancements in digital light processing (DLP) 3D printing, machine learning-optimized microfabrication, liquid metal antenna technologies, and scalable nanocomposite mold development. His work emphasizes industrial feasibility, biocompatibility, and surface engineering. Scientific Awards : Smurfit Kappa Newman Fellowship Award ERC Grants (contextual institutional affiliation) Labs & Collaborations : Based at the UCD Engineering and Materials Science Centre, Dr. Zhang’s research involves partnerships with industry and academic networks, focusing on precision tooling, microfluidic scale-up, and novel material applications (e.g., bulk metallic glasses, bio-plastics).

Andrew HinesView profile

Assistant Professor

• Quality of Experience
• Speech Signal Processing
• Audio Signal Processing
• +5 more

Dr Andrew Hines serves as an Assistant Professor in the School of Computer Science at University College Dublin (UCD) and is a Funded Investigator at the CONNECT Centre. His research focuses on computational modeling for quality assessment across speech, audio, and video systems. Research interests span: Quality of Experience (QoE) metrics development Machine learning applications for health and cryptosystems Speech intelligibility prediction for hearing-impaired individuals Spatial audio streaming quality evaluation His work bridges signal processing theory with practical industry implementations. Hines maintains active industry partnerships, notably with Google on VoIP speech quality metrics and audio codec evaluation for streaming media. He previously represented Ireland on the Qualinet FP7 COST Action management committee, leading machine learning initiatives for QoE modeling, and currently participates in the CryptoAction COST research network. Before academia, he accumulated a decade of industry experience as Director of Engineering in airline and finance software development sectors. His laboratory infrastructure includes the QxLab research group and Dependable Networks project.

Nadia J. ArmstrongView profile

Part-Time Lecturer

• Digital Art
• Artificial Intelligence
• Video Installation
• +4 more

Nadia J. Armstrong is a PhD Researcher at the CONNECT Centre supervised by Dr. Tom O’Dea and a part-time Lecturer on the Creative Futures Academy programme at the National College of Art and Design (NCAD). Her academic foundation includes a first class honours BA in Fine Art Media and Critical Cultures (International) and first class honours MFA in Art in the Contemporary World, both from NCAD. Her research interrogates the commodification of human emotions through machine learning processes, data accumulation systems, and computational frameworks. Armstrong employs performance, 3D composition, AI, and expanded video installation to dissect digital history nodes, cyber identity agency, and socio-political contestations in social space. Her practice treats technological infrastructure as cultural material for examining existential conditions in digital ecosystems. Armstrong’s accolades include: Beta x transmediale 2023 residency Accenture Digital Innovation in Art Bursary (2022) Irish Arts Council Visual Arts Bursary (2022) CYBERNATE residency (2022/23) Goethe-Institut A.I. Residency Award (2021) RDS Visual Arts Award for "DIGITAL NATIVE" (2020) She maintains active exhibition practice with recent presentations including "Altered Terrain" (2023 AR exhibition), Mart Studios Members exhibition (2023), 192nd RHA Annual Exhibition (2022), and "Woman in the Machine" at VISUAL Carlow (2021), demonstrating sustained engagement with digital art communities across European platforms.

• Performance Engineering
• Telecommunication Systems
• Enterprise Software
• +3 more

John Murphy is a Full Professor at the School of Computer Science, University College Dublin. He holds academic positions as an IBM Faculty Fellow and Fellow of multiple professional organizations, including the Institution of Engineering and Technology and Engineers Ireland. His research focuses on Performance Engineering, Telecommunication Systems, and Middleware, with a strong emphasis on cloud computing, distributed systems, and network optimization. Education: B.E. (Electronic Engineering) from University College Dublin (1988), M.Sc. (Electrical Engineering) from California Institute of Technology (1990), and Ph.D. (Electronic Engineering) from Dublin City University (1996). Research Interests: His work spans Performance Engineering, Telecommunication Systems, Enterprise Software, Middleware, Mobile Networks, and Queueing Theory. Notable contributions include energy-efficient cloud resource management and network-aware scheduling in data centers. Publications: Over 200 peer-reviewed articles, including recent work on intelligent computing in IoT, energy-efficient VM mapping, and load balancing in wireless networks. His research trends emphasize cloud optimization, distributed systems performance, and smart city infrastructure. Awards: Recognitions include the Real Time Correlation Engine award and prestigious fellowships. He has supervised 24 PhD students and secured over €9.5M in research grants. Teaching: Coordinates modules on Computer Networking, Databases, and Programming. He advocates for foundational learning to foster adaptability in students. Grants: Includes Horizon 2020 projects like NEO-QE and PRTLI grants for SimSci. Collaborates with industry partners for applied research. Labs: Leads the Performance Engineering Laboratory, advancing research in distributed systems and network performance.

Enda BatesView profile

Assistant Professor

• Spatial Music
• Virtual Reality (VR)
• Spatial Audio
• +4 more

Dr. Enda Bates is an Assistant Professor and Deputy Course Director in the Music and Media Technologies Programme at Trinity College Dublin. He leads research in spatial music, spatial audio for VR, and electroacoustic aesthetics while maintaining active roles as a composer, producer, and performer. His work bridges academic and artistic domains, with notable contributions to immersive media, accessibility in health data design, and interdisciplinary digital humanities projects. Educated at Trinity College Dublin, he completed a PhD titled *The Composition & Performance of Spatial Music* in 2010. His research has been supported by grants from Trinity College Dublin and Rode Microphones, focusing on projects like the Trinity 360 initiative producing immersive 360-degree music videos. He collaborates widely, including with the Spatial Music Collective and on virtual reality adaptations of Samuel Beckett’s works. Research interests span spatial audio technologies, VR audio design, and the aesthetics of contemporary electroacoustic music. He explores the intersection of sound and technology in performance contexts, such as augmented instruments and site-specific compositions. His work on accessibility includes evaluating health data representations for older adults, emphasizing user-centric design principles. Recent publications highlight advancements in ambisonic decoder methodologies, VR audio systems, and interdisciplinary arts. Awards include the Gaudeamus Music Prize shortlist (2009) and Música Viva Competition Prize (2010). His music has been performed globally by ensembles like the RTÉ National Symphony Orchestra and Crash Ensemble. Bates advises on audio engineering projects and leads collaborative initiatives like *Virtual Play, after Samuel Beckett*, merging theater, VR, and sound design. His lab’s work often explores the technical and creative potentials of 360 media and free-viewpoint video.

• Cybersecurity
• Terahertz Communications
• Access Control Systems
• +5 more

Dr. Bernard Butler is a Lecturer in the Department of Computing and Mathematics at the Walton Institute for Information and Communications Systems Science, South-East Technological University (SETU). He holds a PhD in Access Control System Specification (2016) and specializes in cybersecurity, terahertz communications, access control systems, and smart grid security. His research bridges theoretical frameworks with practical applications in 6G networks, vehicular systems, and augmented reality. Affiliations: SETU Walton Institute Key Focus Areas: Terahertz nanonetworks, UAV security, quantum machine learning, and climate change sensing via 6G Research Interests: Terahertz Engineering , Access Control Policies , and Vehicular Network Optimization . He explores disruptive technologies like the Internet of Paint (IoP) for environmental monitoring and AR applications in intelligent transportation systems. His 2024 work on False Data Injection Attacks on UAVs highlights cybersecurity vulnerabilities in drone delivery systems, while 2025's IoP research pioneers smart material-based communication networks. Recent projects include 'ATLAS' (access control system dimensioning) and 'SWAGGER' (mobile/web deployment platforms). Advising: Supervises PhD projects in UAV security, quantum machine learning, and smart grid security. Grants include leadership in two national projects (2008, 2014). Labs/Teams: Active in the Walton Institute's communications systems research group, collaborating on 6G applications and environmental sensing technologies.

John BreslinView profile

Professor

• Data Science
• Artificial Intelligence
• Social Semantics
• +7 more

John Breslin is a Personal Professor in Electronic Engineering at the University of Galway, leading the TechInnovate/AgInnovate programs. His roles include Director of the Insight (Data Analytics) and VistaMilk (AgTech) research centers. He has authored 350+ publications and co-created the SIOC framework, widely used in web applications. His research spans Data Science, AI, Semantic Web, IoT, and Entrepreneurship. He has won multiple awards, including the Best Irish-Published Book and IIA Net Visionary Awards. His teaching spans 25 years, covering topics like Digital Control Systems and Innovation. He co-founded boards.ie, StreamGlider, and leads initiatives in Galway's innovation ecosystem. Research Interests: Data Science, AI, Social Semantics, IoT, Agricultural Technology, and Innovation. He is ranked top in Engineering and Computer Science citations at the University of Galway. His work contributes to UN SDGs related to Industry, Innovation, and Infrastructure. Education: Details not explicitly provided in text. Collaborations include Bosch, Cisco, IBM, and Harvard Medical School. Active in industry partnerships and startups, including the PorterShed Innovation District. Awards: Best Paper Awards, Entrepreneurship Recognition, and Academic Excellence. Supervised nearly 30,000 ECTS across modules, with a focus on graduate and postgraduate tech innovation programs.