جست‌وجوی استاد و پژوهشگر

Barry O'Sullivanمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Constraint Satisfaction
• +۳ مورد دیگر

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
• +۱۰ مورد دیگر

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.

• High Performance Heterogeneous Computing
• Energy Efficient Computing
• Parallel Computing
• +۴ مورد دیگر

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.

Anh Vu Voمشاهده پروفایل

استادیار

• LiDAR
• Urban Science
• Spatial Data Management
• +۴ مورد دیگر

Dr. Anh Vu Vo is an Assistant Professor at University College Dublin's School of Computer Science, specializing in high-scalability algorithms for LiDAR and urban spatial datasets. He holds a PhD from UCD, a Master's from the University of Melbourne, and a Bachelor's from HCMC University of Architecture. Roles : Lecturer/Assistant Professor since 2024, Postdoctoral Research Fellow (2019–2022), Research Scientist at NYU (2018–2019). Research Interests : LiDAR, Urban Science, Spatial Data Management, Distributed Computing, and Big Data. Key projects include CAMEO (Earth Observation platform), UrbanARK (flood risk assessment), and AIMVIE (mangrove mapping). He has authored over 30 peer-reviewed publications and secured grants such as the SFI Future Innovator Prize. Awards : 2022 EODisrupt Winner, 2015 IEEE GRSS Data Fusion Contest First Prize, Australian Endeavour Award. Teaching : Spatial Information Systems, Urban Sensing, and graduate-level courses. His work focuses on integrating LiDAR data with advanced computing frameworks to address urban challenges like flood risk and infrastructure planning.

• Machine Learning
• Algorithm Engineering
• Combinatorial Optimization
• +۳ مورد دیگر

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.

• Mobile Computing
• Distributed Systems
• Decentralized Applications
• +۴ مورد دیگر

Dr. Dimitris Chatzopoulos is an Assistant Professor (Ad Astra Fellow) at the School of Computer Science, University College Dublin. He holds a PhD from The Hong Kong University of Science and Technology and academic qualifications in Computer Engineering from the University of Thessaly, Greece. His research focuses on privacy-preserving systems, AI-driven decentralized applications, mobile computing, blockchain technology, and combating fake news. Education: PhD in Computer Science and Engineering, The Hong Kong University of Science and Technology (2013–2018) MSc in Computer Engineering and Communications, University of Thessaly, Greece Professional Diploma in University Teaching & Learning, University College Dublin Research Interests: Mobile and distributed systems Decentralized AI and blockchain applications Privacy-enhancing technologies Extended reality (XR) interfaces Metaverse infrastructure Awards & Recognition: Heidelberg Laureate Forum Participant (2017) Grants & Projects: "AI-enabled decentralized sensing for mobile and distributed systems" (2023–2026) "DIGITISE: Cross-sector services for societal empowerment" (2024–2027) Ad Astra Fellowship (2020–2027) Teaching & Supervision: Module coordinator for courses such as Blockchain & Decentralisation, Cloud Computing, and Python OOP PhD thesis supervisor

Soumyabrata Devمشاهده پروفایل

استادیار

• Computer Vision
• Machine Learning
• Remote Sensing
• +۶ مورد دیگر

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.

• Plasma Physics
• Fusion Energy
• Tokamak Physics
• +۳ مورد دیگر

Dr. Huw Leggate is a Senior Research Fellow in the School of Physical Sciences at Dublin City University, specializing in plasma physics and fusion energy research. His work focuses on advancing the understanding of plasma behavior in fusion devices such as JET and MAST-U, with particular emphasis on edge plasma dynamics, transport modeling, and ITER-related experiments. He holds a postdoctoral researcher role and contributes to multidisciplinary projects in fusion science. His research interests include plasma surface interactions, impurity transport, and the optimization of fusion reactor components. He has collaborated extensively with international fusion programs, including contributions to JET’s preparation for deuterium-tritium operation and the development of diagnostic tools for edge plasma characterization. His work often intersects with computational plasma physics and the integration of advanced simulation codes (e.g., JOREK, DIVIMP) to model plasma behavior under extreme conditions. Dr. Leggate’s publications reflect a deep engagement with topics such as scrape-off layer filament dynamics, heat transport scaling, and the mitigation of edge localized modes (ELMs). He has also explored the implications of tungsten divertor materials and their degradation under fusion conditions. His research aligns closely with global efforts to achieve practical fusion energy through ITER and DEMO projects. He is affiliated with the Glasnevin Campus at DCU, conducting research in laboratory S120. His contributions to the field include both experimental diagnostics and theoretical modeling, bridging the gap between fundamental plasma physics and applied fusion engineering challenges.

Kieran Herleyمشاهده پروفایل

مدرس

• Parallel Algorithms
• Distributed Computing
• Multicast Routing
• +۲ مورد دیگر

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.

Tania Malikمشاهده پروفایل

مدرس

• High-Performance Heterogeneous Computing
• Parallel and Distributed Computing
• Performance Optimization
• +۳ مورد دیگر

Dr. Tania Malik serves as an Assistant Lecturer in the School of Informatics and Cybersecurity at Technological University Dublin (TU Dublin). She holds a PhD from University College Dublin (UCD) earned in 2017 under the prestigious Irish Research Council Enterprise Partnership Scheme (IRC-EPS) award, establishing her expertise in high-performance computing and related disciplines. Her academic foundation includes doctoral research at University College Dublin, where she was supported by competitive fellowship funding. PhD, University College Dublin (UCD), 2017 (IRC-EPS award) Dr. Malik's research focuses on optimizing computational systems for modern data-intensive applications. Her core interests span High-Performance Heterogeneous Computing, Parallel and Distributed Computing, Performance Optimization, Energy-Efficient Computing, High-Performance Big Data Analytics, and HPC for Machine Learning. She investigates techniques to enhance computational efficiency while reducing energy consumption in large-scale systems, with direct applications in machine learning and big data processing pipelines. Her scholarly recognition includes competitive fellowship support for doctoral research. Irish Research Council Enterprise Partnership Scheme (IRC-EPS) award With extensive experience across Irish and international institutions—including University College Dublin, Dublin City University, National College of Ireland, COMSATS, and NUST Pakistan—Dr. Malik has cultivated significant industry partnerships with Fidelity, IBM, Whizz Systems USA, PSEB, and PYB. Her research program has secured competitive funding from the Irish Research Council (IRC), Science Foundation Ireland (SFI), and European Cooperation in Science and Technology (e-Cost). She actively engages in teaching, student mentorship, and industry collaboration within her academic role. Dr. Malik also contributes to diversity initiatives through active membership in Women in Technology and Science Ireland (WITS), Women in High-Performance Computing (WHPC), Women Leaders in Higher Education (WLHE), Women in Technology United (WITU), and UCD's Women@CompSci group.

Ian Clancyمشاهده پروفایل

مدرس

• Statistical Physics
• Non-linear Physics
• Complex Systems
• +۶ مورد دیگر

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
• +۳ مورد دیگر

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.

• Data Analytics
• Social Network Analysis
• Recommender Systems
• +۴ مورد دیگر

Neil Hurley is an Associate Professor and Head of School in the School of Computer Science at University College Dublin. He holds a BSc and MSc from University College Dublin and a PhD from Trinity College Dublin. Before academia, he worked at the Hitachi Dublin Laboratory from 1989 to 1999, leading research in parallel computing and knowledge-based systems. He joined UCD in 1999 and founded the Information Hiding Laboratory in 2001, focusing on digital content security. His research spans recommender systems, social network analysis, high-performance computing, and data hiding technologies. He has secured over €1 million in research funding from agencies like Enterprise Ireland and the EU. His teaching includes coordinating modules on Artificial Intelligence, Recommender Systems, and Computational Science. He has reviewed for journals such as IEEE Transactions on Image Processing and serves on the EMPS Graduate School Board. His recent work emphasizes scalable recommendation algorithms, privacy-preserving distributed systems, and strategic network analysis.

Martin Craneمشاهده پروفایل

استاد

• Computational Finance
• Complex Systems
• Time Series Analysis
• +۱ مورد دیگر

Martin Crane is Professor and Head of School at Dublin City University School of Computing. Funded Investigator in ADAPT Centre, with PhD in Mechanical Engineering from Trinity College Dublin. Research spans computational finance, complex systems modeling, and high-performance computing applications. Key research areas: Time series analysis in finance/biology Complex systems in finance, immunology, and lifelogging Wavelet methods for market analysis Parallel computing for large-scale simulations Current projects examine cryptocurrency dynamics, healthcare analytics, and brain tumor segmentation using deep learning. Leads FinTech Fusion initiative exploring financial technology applications. Authored significant works on random matrix theory filters for portfolio optimization and agent-based HIV modeling.

Geoff Hamiltonمشاهده پروفایل

دانشیار

• Program Transformation
• Automated Theorem Proving
• Formal Verification
• +۳ مورد دیگر

Dr. Geoff Hamilton is Associate Professor at Dublin City University's School of Computing. His research develops program transformation hierarchies for applications in theorem proving, verification, optimization, and energy-efficient computing. The distillation algorithm—a key contribution—achieves orders-of-magnitude efficiency gains over standard techniques. Work spans automated verification tools, termination provers, security protocol analyzers, and complexity bounds calculators. Recent publications focus on side-channel attacks, concurrency optimization, and tight complexity bounds for loop programs. Teaching includes comparative programming languages, cryptography, and formal methods. Research consistently advances transformation-based approaches for parallelization, verification, and resource analysis. Current directions include smart contract verification and energy-aware program optimization methodologies.