Find Academic Supervisors

• Computer Science
• Networking
• Telecommunications
• +4 more

Prof. Liam Murphy is a Full Professor of Computer Science & Informatics at University College Dublin (UCD) and Director of the Performance Engineering Laboratory. He holds a B.E. from UCD, M.Sc. and Ph.D. from UC Berkeley. His research focuses on performance engineering of networks, software systems, and multimedia transmissions. He has published over 150 peer-reviewed papers and is an IEEE member and Fellow of the Irish Computer Society. Education: B.E. in Electrical Engineering, UCD (1985) M.Sc. & Ph.D. in Electrical Engineering & Computer Sciences, UC Berkeley (1988, 1992) Research Interests: Dynamic resource allocation in networks Cloud computing efficiency Software performance engineering Wireless multimedia systems Quality of Service (QoS) optimization Recent work emphasizes energy-efficient cloud workflows, multi-objective data center optimization, and decentralized traffic simulation. Grants & Awards: Fellow of the Irish Computer Society (2007) Conference Paper Awards (2004, 2002, 2001) Principal Investigator in multiple funded projects (e.g., EU-funded traffic simulation, cloud resource allocation) Advising & Labs: Directed 24 Ph.D. and 8 M.Sc. students. Leads the Performance Engineering Laboratory (PEL), focusing on distributed systems, cloud efficiency, and network performance. Collaborates on industry-relevant projects like crovan (UCD/DCU campus company). Teaching: Coordinates courses on computer science fundamentals, distributed systems performance, and software engineering at UCD.

• 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.

• Artificial Intelligence
• Constraint Programming
• Optimisation
• +10 more

Professor Kenneth Brown is affiliated with the Department of Computer Science at University College Cork (UCC) , Ireland. He holds the academic rank of Professor and is a Principal Investigator at the Insight Centre for Data Analytics and the CTVR (Telecommunications Research Centre) . BSc (Hons) Mathematics, University of Glasgow, 1986 MSc Mathematical Logic and the Foundations of Computation, University of Manchester, 1987 PhD Artificial Intelligence in Engineering, University of Bristol, 1991 His research focuses on Artificial Intelligence, constraint programming, optimisation, and distributed reasoning , with applications in wireless networking, sensor networks, and dynamic resource management . He also works on smart energy systems, data analytics, and human-centric applications. His recent work includes projects under the SFI-funded Insight Centre and Horizon Europe initiatives like GLACIATION and SEISMEC. His publications span topics from wireless sensor network optimization and cognitive radio to constraint-based decision support and AI in emergency management. He has led and contributed to over 15 recent publications in top-tier journals and conferences, showing a strong trend in AI-driven solutions for networked and intelligent systems. IEEE SECON 2015 Best Demonstration 2014 TAOS Best Paper Award in Access Networks and Systems Best paper, SMARTGREENS 2013 Enterprise Ireland Lifescience and Food Commercialisation Award Best Application Paper, AI2008 Best Application Paper, AI2006 Best paper nomination, ECAI 2004 Best Paper, Intl Conf AI in Design Professor Brown has supervised numerous PhD and MSc students in areas including constraint programming, sensor networks, evacuation modeling, and smart buildings. He has secured significant research funding from SFI, Enterprise Ireland, and IRCSET. He is actively involved in research leadership, serving as Deputy Director of Insight@UCC and PI in multiple national and international projects. He is a member of research groups involved in GLACIATION (green, responsible data operations), SEISMEC (human-centric industry), and SMARTeBuses . His lab supports a team of doctoral students and research staff working on AI, networking, and data analytics for real-world applications.

Barry O'SullivanView profile

Professor

• Artificial Intelligence
• Machine Learning
• Constraint Satisfaction
• +3 more

Professor Barry O'Sullivan is a leading academic and industry expert in artificial intelligence at University College Cork , where he serves as a full professor in the School of Computer Science & IT . He directs the Insight Centre for Data Analytics and the SFI Centre for Research Training in AI, and holds influential advisory roles at Europol's GRACE project, Leuven.ai institute, and the Computational Sustainability Network. His €300m+ R&D funding achievements and 15+ recent publications highlight his technical and societal impact. Co-founder and Chief AI Officer, Stimul.ai Member of University College Cork Governing Body Vice Chair, European Commission High-Level Expert Group on AI Former President, European AI Association His research spans AI ethics , machine learning , and computational sustainability , with recent work focusing on explainable AI for medical diagnostics, energy-efficient scheduling in manufacturing, and human-AI collaboration mechanisms. His publications reveal expertise in constraint programming, anomaly detection, and multilingual reasoning systems. Notable awards include fellowships from AAAI, EurAI, and the Royal Irish Academy, alongside leadership roles in AI policy committees for the European Commission and Irish health research ethics. He leads a team of PhD researchers at UCC, including Marco Dalla and Sharmi Dev Gupta, while directing major European AI initiatives like the ALTAI assessment framework.

• Discrete Mathematics
• Number Theory
• Algebraic Geometry
• +10 more

Professor Gary McGuire is a Full Professor in the School of Mathematics and Statistics at University College Dublin (UCD), specializing in discrete mathematics, number theory, algebraic geometry, and cryptography. He holds a PhD from the California Institute of Technology and has been a central figure in advancing research in finite fields and their applications. BSc, University College Dublin MSc, University College Dublin PhD, California Institute of Technology His research focuses on algebraic structures over finite fields, including Galois theory, permutation polynomials, error-correcting codes, and quantum codes. He has made significant contributions to the understanding of supersingular curves, L-polynomials, and lattice-based cryptanalysis. His work spans theoretical advances and practical applications in cryptography and computational mathematics. The recent publications reflect a strong trend in algebraic and computational number theory, with emphasis on Galois groups of linearized polynomials, quantum code construction, and discrete logarithm algorithms. His work often involves deep connections between algebraic geometry and coding theory, particularly in the construction of MDS and quantum codes from generalized monomial-Cartesian and algebraic geometry codes. Notable scientific awards and recognitions include: Best Paper Award at CRYPTO 2013 Invited Speaker at the 12th International Conference on Finite Fields (2015) Invited Speaker at the 25th British Combinatorial Conference (2015) Invited Session Speaker at the AAAS Annual Meeting (2014) Speaker at multiple international workshops on finite fields, cryptography, and polynomials Professor McGuire actively supervises PhD students and has coordinated key modules such as Galois Theory, Cryptography, and Numbers & Functions. He has secured research grants, including one on the simulation of photo-electronic excitation in nanofilms. His most famous contribution is the proof that no 16-clue Sudoku puzzle exists, achieved through a novel hitting set enumeration algorithm. He is a principal investigator in computational and theoretical mathematics with ongoing collaborations across Europe. He is a member of research teams focused on finite field applications, cryptographic protocols, and algebraic coding theory. His lab-like collaborative environment involves work with postdocs and researchers on projects related to discrete logarithm computation, polynomial factorization, and quantum code design.

• Machine Learning
• Algorithm Engineering
• Combinatorial Optimization
• +3 more

Dr. Deepak Ajwani is an Assistant Professor in the School of Computer Science at University College Dublin . His research focuses on leveraging machine learning techniques for solving combinatorial optimization problems, with expertise in algorithm design, algorithm engineering, and graph algorithms. He holds a PhD from the University of Saarland, Germany, and has held postdoctoral positions at Aarhus University (Denmark) and University College Cork (Ireland). He also worked at Nokia Bell Labs (2012–2018) on learning systems for unstructured content analysis. Dr. Ajwani has received over 50 peer-reviewed publications in top-tier conferences and journals. He serves on the editorial board of the Machine Learning journal and is a frequent senior program committee member for conferences like WWW, IJCAI, AAAI, and ALENEX. He is a funded investigator at the SFI Centre for Research Training in Machine Learning (ML-Labs) . His teaching excellence has been recognized through multiple nominations for the UCD Teaching and Learning Award . His students have won the Franz Geiselbrechtinger Medal (2023, 2024) for best final-year projects in theoretical computer science. Key grants include the Irish Research Council and IBM Research Grant (2010–2012) for graph partitioning techniques in exascale computing. His research explores integrating machine learning with optimization algorithms, graph neural networks, and algorithm engineering for real-world applications.

Kieran HerleyView profile

Lecturer

• Parallel Algorithms
• Distributed Computing
• Multicast Routing
• +2 more

Dr. Kieran Herley is a Lecturer in the School of Computer Science and Information Technology at University College Cork. Educated at UCC and Cornell University, he has taught at UCC since 1990. His research centers on parallel and distributed computing, algorithm design, and network routing. His key interests include multicast routing on mesh networks, shared memory implementation, and comparative analysis of parallel computation models like BSP and LogP. Dr. Herley's work addresses fundamental challenges in deterministic algorithms and network efficiency for high-performance systems. Publications highlight innovations in parallel backtrack search, shared memory architectures, and communication models. Consistent themes include optimization of distributed algorithms and theoretical frameworks for parallel computing. Dr. Herley teaches courses on algorithms, databases, and compilation. He has served on program committees for Euro-Par and ESA conferences, contributing to advancements in parallel computing methodologies.

Muhammad YahyaView profile

Researcher

• Optical Network-on-Chip (ONoC)
• Cybersecurity
• Heuristic Optimization Algorithms
• +2 more

Muhammad Yahya is a researcher at Nanjing University of Aeronautics and Astronautics with affiliations to institutions like Universiti Malaysia Terengganu and Norwegian University of Life Sciences. His work bridges optical network-on-chip (ONoC) and cybersecurity domains. H-index: 21 Total citations: 1,400+ Research Interests: Focus on photonic interconnects for manycore processors, heuristic optimization algorithms for crosstalk reduction, and security vulnerabilities in optical networks. Key projects include: Designing non-blocking optical switches with reduced power consumption Developing DPA-resistant cryptographic architectures for lightweight ciphers Creating heuristic fusion mapping algorithms combining PSO and SA Publication Trends: Recent articles (2018-2023) demonstrate expertise in optical router design , fault analysis of encryption protocols, and machine learning applications to network optimization. Technical Contributions: Invented the PSO_SA algorithm for crosstalk optimization, HoneyComb ROS reconfigurable switches, and two-domain MATLAB frameworks for computational mathematics.

• Artificial Intelligence
• Cloud Computing
• Internet of Things
• +7 more

Aamir Akbar serves as an Assistant Professor in the Department of Computer Science & Information Systems at Abdul Wali Khan University Mardan (AWKUM), where he also co-directs both the AWKUM AI Lab and AWKUM Robotics initiatives while coordinating final year projects. His academic journey culminated in a PhD from Aston University, Birmingham, UK, with research focused on energy-efficient methods for hybrid mobile cloud computing. His educational background includes a PhD in Computer Science from Aston University (2015-2019, awarded February 2020), where his dissertation explored energy-efficient approaches for hybrid mobile cloud computing systems. Dr. Akbar's research spans multiple cutting-edge domains in computer science, with particular emphasis on Artificial Intelligence , Cloud and Fog Computing , Internet of Things , and Software Defined Networks . His multidisciplinary approach combines evolutionary computation, multi-objective optimization, and machine learning to develop resource-efficient intelligent systems. His work frequently addresses challenges in Cyber-Physical Systems, Mobile-Cloud Computing, and IoT/IoV applications, demonstrating strong practical relevance to real-world problems. Analysis of his recent publications (2021-2024) reveals a clear research trajectory toward increasingly sophisticated AI applications in networking and distributed systems. His work shows strong focus on reliability, energy efficiency, and security across multiple domains including medical IoT, smart cities, and industrial automation. The growing citation impact (612 total citations, h-index: 14) demonstrates increasing recognition of his contributions to these fields. Dr. Akbar maintains active presence in the research community with 19 total publications showing accelerating output in recent years (6 in 2021, 2 in 2022, 5 in 2023, and 2 in 2024). His Google Scholar profile reflects substantial impact with an h-index of 14 and i10-index of 16. As an educator and researcher, Dr. Akbar brings both academic rigor and industry experience to his role. His technical expertise spans the full stack of modern computing systems, from frontend development (HTML, CSS, Angular, React) through backend frameworks (Flask, Django, Node.js) to database systems (MySQL, PostgreSQL, MongoDB) and cloud infrastructure (AWS, Kubernetes, Docker). This comprehensive skill set enables him to bridge theoretical research with practical implementation. He leads research initiatives through the AWKUM AI Lab and AWKUM Robotics, providing students with opportunities to engage in cutting-edge projects that combine theoretical foundations with real-world applications. His GitHub activity shows ongoing engagement with AI and systems development projects, including repositories focused on neural networks, Python programming, and network simulation.

• Healthcare Operations
• Supply Chain Optimization
• Artificial Intelligence
• +3 more

Ali Ala is a Post Doc Research Fellow Lvl I at the School of Mechanical and Materials Engineering, University College Dublin (UCD), where he works on the ReAMPS project addressing medicines shortages. He holds a PhD in Industrial Engineering and Management Science from Shanghai Jiao Tong University (2020) and an M.Eng from Wuhan University of Technology (2014). Previously, he served as a researcher at the Tokyo Institute of Technology (2018–2019) and a research fellow at INTI International University, Malaysia (2021). Education: PhD in Industrial Engineering and Management Science, Shanghai Jiao Tong University (2020) M.Eng in Industrial Engineering, Wuhan University of Technology (2014) Research Interests: Healthcare operations optimization, artificial intelligence applications in supply chains, multi-criteria decision-making, and sustainable energy systems. He has published extensively on topics like healthcare scheduling, supply chain resilience, and IoT-driven precision farming. Grants & Projects: Principal Investigator: ReAMPS Project (National Challenge Fund Programme, Ireland, 2024) SGC Scholarship (Chinese Government, 2014–2020) Professional Activities: Peer reviewer for journals like Applied Soft Computing and Engineering Applications of Artificial Intelligence ; committee member of the European Operations Management Association (EurOMA) and INFORMS. He has also served on doctoral thesis panels and interview committees.

• Information Visualization
• Graph Drawing
• Combinatorial Optimization
• +3 more

Patrick Healy serves as an Associate Professor in the Department of Computer Science & Information Systems within the Faculty of Science and Engineering at the University of Limerick. He is an active member of Lero – the Irish Software Research Centre , contributing to Ireland's national software research initiatives. His research spans Information Visualization, Graph Drawing, Combinatorial Optimization, and Routing/Scheduling problems. He specializes in developing algorithms for graph layout, table formatting, and upward planarity testing, with recent work expanding into machine learning robustness, medical AI diagnostics, and occlusion handling in computer vision. His fingerprint analysis reveals deep expertise in digraph theory (100%), planarity (76%), edge optimization (71%), and combinatorial optimization (51%). Current research trends show a significant shift toward applied AI since 2022, with 12 of his 15 most recent publications focusing on neural network robustness, medical diagnostics, and data augmentation techniques. Earlier work established foundations in graph theory and document engineering. He has supervised numerous research projects through Lero and maintains active collaborations across European institutions, particularly in software engineering and AI applications. His laboratory work centers on the Visualisation and Algorithm Design Group at UL, focusing on interpretable AI systems and robust visualization frameworks.

Gregory ProvanView profile

Professor

• Complex Systems
• Artificial Intelligence
• Diagnostics
• +3 more

Professor Gregory Provan is a Full Professor and Programme Coordinator for BSc Data Science and Analytics at University College Cork's School of Computer Science and Information Technology. He directs the Complex Systems Laboratory and holds a PhD from the University of Oxford, with prior academic appointments at the University of Pennsylvania. His educational journey includes: BSE from Princeton University MSc from Stanford University DPhil from University of Oxford This foundation supports his interdisciplinary research approach. Professor Provan's research spans: complex systems design and analysis with applications in: Embedded diagnostics algorithms for large-scale systems Stochastic model-based diagnosis frameworks Automated benchmark model generation Sustainable energy system optimization Co-design of embedded systems His work bridges artificial intelligence, data analytics, and network architectures to solve real-world engineering challenges. Analysis of his extensive publication record reveals core themes: Advancements in model-based diagnosis and control Computational methods for complex systems Applications in sustainable energy and building automation Innovations in stochastic optimization and machine learning His recent work increasingly focuses on cybersecurity for cyber-physical systems and explainable AI. Professor Provan has secured significant research funding including: Science Foundation Ireland grants totaling over €1.2M Industry partnerships with Tyndall National Institute Enterprise Ireland support for competence centers His research group addresses fundamental challenges in complex systems engineering. He has supervised numerous doctoral candidates to completion, including: Jun Wang (Modeling real-world complex systems) Alie El-Din Mady (Networked control systems) Margarita Razgon (Constraint satisfaction problems) Ma Ji (Uncertainty visualization) Current doctoral researchers continue work on wireless sensor networks and analog system diagnosis. Honors include the 2008 Best Paper Award from the IEEE Prognostics and Health Management Conference for his work on approximation techniques in model-based diagnostics. Professor Provan leads the Complex Systems Laboratory which focuses on: Modeling and analysis of sustainable energy systems Diagnostics and control of large-scale networks Embedded system co-design The lab maintains collaborations with international research institutions and industry partners.