Find Academic Supervisors

• Augmented Reality
• Virtual Reality
• Mixed Reality
• +6 more

Abey Campbell is an Assistant Professor in Computer Science at the School of Computer Science, University College Dublin. He holds roles such as Deputy Programme Director for Computer Science, Director of UCD VR Lab, and 1st Year Stage Coordinator. His research focuses on Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), and Multi-Agent Systems with applications in education, healthcare, and human-computer interaction. Campbell has coordinated modules like Augmented and Virtual Reality, Computer Graphics, Game Development, and Mobile Computing. He earned his BSc and PhD in Computer Science from University College Dublin. His work explores touchless interaction technologies, machine learning agents in STEM education, and ethical implications of emerging technologies. Notable contributions include RenderKernel for real-time rendering systems and studies on AR's role in decision support systems. Campbell has secured a grant from Enterprise Ireland for collaborative design documentation and participates in professional activities like peer reviewing for Frontiers in Virtual Reality and IEEE conferences. His collaborative projects include developing AR tools for veterinary training and evaluating immersive VR experiences in nursing education. The UCD VR Lab under his direction focuses on applied research in spatial computing and interactive systems.

Sabin TabircaView profile

Senior Lecturer

• Artificial Intelligence
• Data Analytics
• Algorithmics
• +6 more

Dr. Sabin Tabirca is a Senior Lecturer at the School of Computer Science and Information Technology, University College Cork (UCC). He holds a BSc from Bucharest University and a PhD from Brunel University. His research focuses on Artificial Intelligence, Data Analytics, Algorithmics, Interactive Media, and HCI, with applications in computational cancer modeling, mobile health (mHealth), and parallel computing. He coordinates MPT Activities and is affiliated with the CRR Group and BCRI Centre. Notable awards include UCC's President Award for Innovation in Teaching (2007), IT@Cork Leader Award (2008), and UCC Staff Recognition Award (2013). His teaching includes modules like Parallel and Grid Computing, Mobile Application Design, and Graphics for Interactive Media. Dr. Tabirca has supervised over 70 MSc students and numerous PhD candidates, many of whom now hold academic and industry roles globally. His research includes developing mHealth apps for cystic fibrosis patients, 3D cancer visualization tools, and frameworks for mobile parallel computing. Publications span mHealth design pipelines, cancer prediction models, and mobile gaming for health education. He actively engages in interdisciplinary projects, blending computer science with medical and biological applications.

Victor LazzariniView profile

Professor

• Computer Music
• Digital Signal Processing
• Electroacoustic Music
• +3 more

Victor Lazzarini is a Professor of Music at Maynooth University, Ireland, specializing in computer music and audio signal processing. He holds a BMus from Universidade Estadual de Campinas (UNICAMP), Brazil, and an AMusD from the University of Nottingham, UK. His research spans electroacoustic music, digital signal processing, and music technology. He leads the Csound project, a widely used sound and music computing system, and authored libraries like Aulib and Aurora. Education: Bachelor of Music (BMus), UNICAMP, Brazil Advanced Music Degree (AMusD), University of Nottingham, UK His research interests include sound synthesis, computer music languages, and the intersection of music with technology. He has authored over 150 peer-reviewed publications and books such as Spectral Music Design: A Computational Approach (Oxford UP, 2021) and co-edited volumes like Ubiquitous Music Ecologies (Routledge, 2020). His work bridges academic and industrial sectors through projects like the Enterprise-Ireland-funded commercialization initiative. Prof. Lazzarini’s contributions to music technology include pioneering tools like Csound, which enable real-time audio synthesis and processing. His articles span topics from digital filter design to historical computer music archaeology, reflecting his expertise in both theoretical and applied domains. Awards: AIC/IMRO International Composition Prize (2006) He advises on interdisciplinary projects such as the BeatHealth initiative, integrating ubiquitous computing and music. His creative output includes electroacoustic compositions performed globally and released on labels like FarPoint Recordings. Lazzarini actively collaborates with international teams, contributing to conferences like DAFx and ICMC, and leads initiatives like the Ubimus (Ubiquitous Music) research network.

• Artificial Intelligence in Healthcare
• Power Electronics
• Digital Control Systems
• +1 more

Anthony Kelly serves as a Postdoctoral Research Fellow in the Department of Electronic and Computer Engineering within the Faculty of Science and Engineering at the University of Limerick, Ireland, with his office located in E2-006. His affiliation spans both engineering and healthcare domains through interdisciplinary research initiatives. His research demonstrates dual expertise in artificial intelligence applications for healthcare and advanced power electronics. In healthcare AI, he develops interpretable mental health models, diabetes management chatbots, and comorbid condition interventions with emphasis on clinician trust and safety evaluation. In power systems, he pioneers digital control techniques for DC-DC converters, FPGA power management, and machine learning-integrated circuit designs. This bifurcated focus reveals a strategic transition from hardware-centric research (2005-2019) toward AI-health convergence (2024-2025). Analysis of his 15 most recent publications shows a pronounced shift toward healthcare AI since 2024, with 80% of current work addressing mental health modeling, diabetes chatbots, and comorbid condition management. Earlier publications (2009-2019) consistently focused on power electronics innovations including current-sharing algorithms, adaptive controllers, and FPGA-based systems, establishing foundational expertise later applied to healthcare technology development.

• Pervasive Computing
• Wireless Sensor Networks
• Healthcare Informatics
• +3 more

John Herbert is a Senior Lecturer in Computer Science at University College Cork (UCC), Ireland. His research focuses on pervasive computing, wireless sensor networks, and healthcare informatics, with notable projects like the CARA framework for falls assessment in the elderly. He holds a PhD in Computer Science from Cambridge University and has held visiting roles at institutions including SRI International and the University of Cambridge. Education: BSc (Experimental Physics), MSc (Experimental Physics), Postgraduate Diploma (Computer Science) from UCC; PhD (Computer Science) from Cambridge University. Research Grants: Led projects funded by Science Foundation Ireland (€163,726) and the Irish Research Council (€71,250), focusing on cloud computing and healthcare applications. His work emphasizes context-aware systems, data quality in medical environments, and real-time analysis. Selected awards include an International Fellowship from Digital Systems Research Center (1989) and visiting fellowships at Cambridge (2008-2009). Teaching: Courses include Advanced Software Engineering, Formal Methods, and Model-Based Software Development. Outreach: Advisor to award-winning student teams (e.g., IEEE mobile app contest) and collaborator with industry partners in China and Europe.

• Edge Computing
• Cloud Computing
• Artificial Intelligence
• +7 more

Hadi Tabatabaee is an Assistant Professor at the School of Computer Science, University College Dublin (UCD), leading the Sustainable Orchestration in Computing Continuum (SOC² Lab). His research focuses on sustainable orchestration of services across edge-cloud environments, emphasizing energy efficiency, carbon-aware systems, and AI-driven applications like large language models (LLMs). Key roles include Associate Editor for IEEE Access and Management Committee member of COST Action CA22151 (CYPHER). He holds a PhD in Computer Engineering from the University of Isfahan and has held academic positions at Maynooth University, Shahid Beheshti University, and Trinity College Dublin's CONNECT research program. Education: PhD (Computer Engineering, University of Isfahan), MSc (Computer Engineering), with a research visit at TU Delft (2010-2011). Certifications include Epigeum's Research Leadership and Research Integrity courses. Languages: Persian (fluent), Azerbaijani (spoken). Research Interests: Edge-cloud continuum, dynamic service placement, distributed AI workloads, LLM optimization, and sustainable resource management. Recent work includes zero-trust vehicular networks, parallel algorithms for recommender systems, and geospatial event processing. Awards: None explicitly listed, though his contributions include over 20 journal articles in IEEE/Elsevier/Springer venues. Professional Activities: IEEE Senior Member, TPC member for IEEE conferences, and reviewer for multiple journals. Teaching: Coordinates/teaches Cloud Computing, Computer Networks, and Principles of Computer Organization at UCD.

• High-Performance Computing
• Energy-Efficient Computing
• Parallel and Distributed Systems
• +5 more

Ravi Reddy Manumachu is an Assistant Professor in the School of Computer Science at University College Dublin (UCD), Ireland. He holds a B.Tech from IIT Madras (1997) and a PhD in Computer Science from UCD (2005), specializing in high-performance heterogeneous computing and energy-efficient systems. His research focuses on optimizing performance and energy efficiency in modern heterogeneous platforms like clouds, grids, and supercomputers through novel models and algorithms. Key contributions include functional performance/energy models, energy-prediction frameworks, and extensions like Heterogeneous MPI and ScaLAPACK for heterogeneous clusters. He has published over 69 articles in top journals/conferences, with recent works addressing data transfer energy measurement, scalable allreduce algorithms (SUARA), and portable programming models (OpenH). Professional roles include Assistant Professor at UCD (2023–present), SEAI Research Fellow (2022–2023), and prior industrial experience at Ansys, Siemens, and IONA Technologies. He has certifications in university teaching, GDPR, and research integrity. Languages include English (fluent), Telugu, and Hindi. Research trends emphasize bi-objective optimization (performance-energy), hardware heterogeneity challenges, and scalable communication algorithms for deep learning. His work addresses energy non-proportionality in CPUs and GPU-CPU interactions, with practical solutions for real-world applications like matrix operations and gene sequencing.

• 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.

• Multimedia Quality of Experience
• Machine Learning
• Immersive Media
• +3 more

Dr. Helard Becerra is an Assistant Professor in the School of Computer Science at University College Dublin (UCD). He holds a PhD from the University of Brasília and has held postdoctoral roles at UCD's Insight Centre for Data Analytics and Samsung R&D Institute Brazil. His research focuses on multimedia quality assessment (audio/video/speech) and AI-driven healthcare solutions for stroke rehabilitation. Key contributions include developing NAViDAd (a deep learning-based quality metric) and predictive models for stroke recovery outcomes. Education: B.Sc. (UNSAAC, Peru, 2010); M.Sc. & Ph.D. (UnB, Brazil, 2013/2019). Professional experience includes roles at Samsung (2019), DIT (2017-2018), and leadership in EU projects like Precise4Q (Horizon 2020). Research interests span: 1) Perceived quality in multimedia systems, 2) Explainable AI for healthcare, 3) Predictive modeling in stroke rehabilitation. Notable work includes gradient boosting models for social risk prediction and Elo rating systems for personalized therapy. Teaching responsibilities include coordinating modules on Software Engineering, Parallel Computing, and Programming. He actively supervises graduate students and serves on UCD's Equality, Diversity & Inclusion Committee. Awards include the 2019 Best Student Paper Award at International Symposium on Electronic Imaging. He reviews for top conferences (ACM MMSys, IEEE ICIP) and journals (IEEE Access, IEEE Signal Processing Letters).

Barak PearlmutterView profile

Professor

• Adaptive systems
• Automatic differentiation
• Theoretical neurobiology
• +8 more

Professor Barak Pearlmutter is affiliated with Maynooth University in the Faculty of Science & Engineering . His research spans multiple domains including automatic differentiation , neural networks , machine learning , and neuroscience . He has contributed significantly to adaptive systems , brain imaging , and programming language design . Research Interests include: Adaptive systems, automatic differentiation, theoretical neurobiology, neural networks, machine learning, acoustic source separation/localization, neuroscience, brain imaging, programming language design, and computational neuroscience. Publications focus on applying algorithmic differentiation to machine learning, developing neural ODE models for biomedical signals, advancing sparse NMF techniques, and integrating functional programming with numerical methods. Collaborations span institutions like MIT, Oxford, and IEEE societies, with work in brain-computer interfaces , MEG source localization , and neuromodulation for tinnitus treatment. Technical Contributions include the DiffSharp AD library for .NET languages and foundational work on reverse-mode automatic differentiation in functional frameworks. His 2018 Journal of Machine Learning Research survey on AD remains a seminal reference in the field. Application Areas cover biomedical signal processing , optical brain-computer interfaces , cognitive modeling , and neural code optimization . His work intersects computer science, neuroscience, and mathematical computing through sparse decomposition and probabilistic modeling .

• Structural geology
• Tectonics
• Field studies
• +6 more

Dr. Vincent Roche is a Research Fellow at the University College Dublin in the School of Earth Sciences . His research focuses on structural geology, tectonics, and induced seismicity, with expertise in seismic interpretation and geomechanical modeling. Research Interests : 3D fault geometry and segmentation Induced seismicity mechanisms Fluid-rock interactions in fault zones Petrophysical and mechanical rock properties Geothermal system structural controls Scientific Contributions : Analyzed fault system evolution across multiple tectonic settings using high-resolution seismic data and field studies. Developed models for stress distribution in layered rocks and displacement transfer in conjugate fault systems. Awards : Marie Skłodowska-Curie Fellowship (2021-2023) under Horizon 2020 Professional Activities : Regular reviewer for journals including Environmental Earth Sciences , Geophysics , and SPE Journal . Utilizes geomodeling software such as Traptester, Move 3D, and Gocad for structural analysis.

• High Performance Heterogeneous Computing
• Energy Efficient Computing
• Parallel Computing
• +4 more

Alexey Lastovetsky is an Associate Professor at the School of Computer Science, University College Dublin (UCD), where he is the founding Director of the Heterogeneous Computing Laboratory (HCL). He holds a PhD from the Moscow Aviation Institute and a Doctor of Science (Habilitation) from the Russian Academy of Sciences. His research focuses on high-performance heterogeneous computing, energy-efficient computing, and parallel algorithms for modern architectures. He has published over 175 peer-reviewed papers and authored influential monographs in the field. Education: PhD (Moscow Aviation Institute), Doctor of Science (Russian Academy of Sciences) Affiliations: UCD since 2001; previously Senior Scientist at Lomonosov Moscow State University (1989–1994) and Principal Scientist at the Russian Academy of Sciences (1995–1999) His research interests span heterogeneous computing , energy-efficient systems , and high-performance parallel algorithms . He has developed novel methodologies for workload distribution optimization, energy modeling, and communication performance analysis. His work on the OpenH programming model and SUARA communication algorithm exemplifies his contributions to scalable parallel computing. He has secured over €4.5M in grants , including four prestigious SFI Investigator awards. His recognition includes being ranked in the Stanford/Elsevier Top 2% Scientists list since 2020 and a ScholarGPS Highly Ranked Scholar distinction. He has organized over 300 international conferences and serves on editorial boards of journals like Journal of Parallel and Distributed Computing . Teaching responsibilities include coordinating modules on High-Performance Computing , Parallel Computing , and UNIX Programming . His lab, HCL, is a global leader in heterogeneous computing research, advancing energy-efficient and scalable solutions for modern HPC platforms.

Soumyabrata DevView profile

Assistant Professor

• Computer Vision
• Machine Learning
• Remote Sensing
• +6 more

Soumyabrata Dev is an Assistant Professor in the School of Computer Science at University College Dublin (UCD), where he leads the THEIA lab focusing on interdisciplinary research in computer vision, machine learning, and remote sensing. His work addresses challenges in climate science, environmental monitoring, solar forecasting, and healthcare. He holds a PhD from Nanyang Technological University (Singapore) and has held postdoctoral roles at Trinity College Dublin and ADAPT SFI Research Centre. His education includes a B.Tech. (summa cum laude) from National Institute of Technology Silchar, India, and a visiting doctoral experience at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. Prior to academia, he worked as a network engineer at Ericsson India (2010–2012). Research interests span image processing, environmental data analytics (e.g., air/water quality), solar energy forecasting, and AI-driven solutions for sustainable development. He collaborates globally with institutions in academia, industry, and government, aligning with UCD’s strategic goals for impactful innovation. He is an SFI Funded Investigator at ADAPT SFI and a UCD Climate Fellow (2024–2026). His scientific awards include the 2024 Stanford/Elsevier Top 2% Scientists List. He advises numerous PhD/MSc students on topics like coastal monitoring, air quality modeling, and AI for sustainability. THEIA Lab’s projects include solar irradiance forecasting, knowledge graph-based climate data platforms, and blockchain-enhanced healthcare systems. He teaches modules on Operating Systems, Wireless Sensor Networks, and Augmented/Virtual Reality. His work bridges theory and application, emphasizing real-world impact in climate action and renewable energy.

Ian ClancyView profile

Lecturer

• Statistical Physics
• Non-linear Physics
• Complex Systems
• +6 more

Ian Clancy is a Lecturer at the University of Limerick , affiliated with the Faculty of Science and Engineering . He serves as the Course Director for the LM125 Physics (Common Entry) program and has previously held the same role for the BSc and MSc in Applied Physics. Education: PhD in Physics, University of Limerick (1999–2004) BSc in Applied Physics, University of Limerick (1995–1999) Dr. Clancy’s research focuses on statistical and non-linear physics , with applications in complex systems , emergent behavior , and dynamic phase transitions . His work spans modeling earthquakes, electromigration in interconnects, inkjet printing for conductive interconnects, pore growth in Indium-Phosphide, and the stability of polymers with embedded gold nanoparticles. He also collaborates on projects involving granular media and nanotechnology . His recent publications highlight expertise in electron microscopy simulation software (TEMGYM Basic and Advanced) and applications in nanomaterials and physics education . He contributed to the Professional Diploma in Teaching Physics , which received funding to train secondary school teachers in physics accreditation. Teaching includes modules like PH4005 Introduction to Computational Physics , PH4171 Mechanics , and PH4042 Thermal Physics , emphasizing programming, numerical methods, and practical lab experiments.

• Sustainable Orchestration in Edge-Cloud Environments
• Multi-Cloud Workload Distribution
• Large Language Models (LLMs) Deployment
• +3 more

Dr. Hadi Tabatabaee Malazi is an Assistant Professor at the University of College Dublin (UCD), leading the Sustainable Orchestration in Computing Continuum (SOC² Lab). He holds an Orcid identifier (0000-0002-2960-6896) and has extensive academic experience across institutions like Maynooth University, Shahid Beheshti University, and Trinity College Dublin. His research focuses on sustainable computing, edge-cloud continuum orchestration, AI/ML deployment (e.g., LLMs), and energy efficiency. He is a Senior Member of IEEE, serves as an Associate Editor for IEEE Access, and chairs the COST Action CA22151 (CYPHER) on decarbonizing energy-intensive industries. Education: PhD (2012): University of Isfahan (Computer Engineering) MSc (prior to 2012): University of Isfahan Research Visit (2010-2011): Delft University of Technology Research Interests: Sustainable edge-cloud systems, AI-driven workload optimization, carbon-aware resource management, distributed LLMs, and IoT interoperability. Key contributions include over 20 journal articles in IEEE, Elsevier, and Springer venues, with topics ranging from vehicular network security to smart city event processing. Professional Activities: Committee member of COST Action CA22151, IEEE Access Associate Editor, and Technical Program Committee member for IEEE conferences. Authored certifications on research leadership and research integrity from Epigeum. Labs/Teams: SOC² Lab (UCD), leading projects on edge-cloud sustainability and AI application deployment.