جست‌وجوی استاد و پژوهشگر

Nikela Papadopoulouمشاهده پروفایل

مدرس

• High-Performance Computing (HPC)
• Energy Efficiency
• Sustainable Computing
• +۳ مورد دیگر

Nikela Papadopoulou is a Lecturer (Assistant Professor) in Low Carbon and Sustainable Computing at the University of Glasgow's School of Computing Science. She is affiliated with the GLAsgow Systems Section and focuses on optimizing high-performance computing (HPC) systems for reduced environmental impact, including performance modeling, application optimization, and energy-efficient resource management. Her work also explores co-design strategies for machine learning workloads. Education: PhD in Electrical and Computer Engineering from National Technical University of Athens (NTUA). Postdoctoral research at Chalmers University of Technology (Sweden) and NTUA, contributing to European projects like ACTiCLOUD, EuroEXA, and HiDALGO. Member of ACM and HiPEAC. Research Interests: HPC systems optimization, energy efficiency in computing, sustainable computing practices, machine learning co-design, and parallel algorithm development. Teaching: Currently teaches Systems Programming (COMPSCI4081) and Internet Technology (COMPSCI5012) at the MSc level. Advising: Supervises Shuxuan Li on FPGA-based compiler transformations for sequence models. Active in grant-funded projects related to HPC and sustainable computing. Labs/Teams: Active contributor to the GLAsgow Systems Section, focusing on HPC and low-carbon computing innovations.

• Neural Networks
• Spiking Neural Networks
• Many-Core Processing
• +۷ مورد دیگر

Simon Davidson is a Research Fellow specializing in Advanced Processor Technology, with a focus on neural network hardware implementations and spiking neural network architectures. His work is closely associated with the SpiNNaker project, a massively parallel computing platform designed for large-scale neural simulations. Dr. Davidson's research spans multiple critical areas at the intersection of computer architecture and neuroscience: Spiking Neural Network Hardware Implementation Many-Core Processor Architectures Power Management for Neural Computing Systems Event-based Computation Paradigms FPGA-based Neural Hardware Digital Implementation of Biological Neural Models His recent publications reveal a progression from foundational tool development (SpiNNTools, spiNNlink) to comparative analysis of neural network approaches on hardware platforms. The research demonstrates increasing sophistication in handling million-core systems and addressing challenges in neural network deployment on digital hardware. Dr. Davidson has made substantial contributions to the SpiNNaker ecosystem, developing critical components including interconnect systems, execution engines, and software stacks that enable large-scale neural network simulations with biologically plausible timing constraints.

• Computational Statistics
• Machine Learning
• Bayesian Inference
• +۳ مورد دیگر

Saifuddin Syed is a Florence Nightingale Bicentenary Research Fellow at the University of Oxford's Department of Statistics, supervised by Arnaud Doucet and funded by the CoSInES project. His research focuses on computational statistics and machine learning, particularly scalable Bayesian inference, Monte Carlo methods, and non-reversible parallel tempering. He completed his PhD in Statistics at the University of British Columbia under Alexandre Bouchard-Côté. Currently, he contributes to the Next Generation Event Horizon Telescope (ngEHT) collaboration, improving algorithms for modeling and imaging supermassive black holes. Research interests include parallel tempering, sequential Monte Carlo, information geometry, and statistical physics. His work spans methodological development in MCMC schemes and applications in complex systems. He is affiliated with the Computational Statistics and Machine Learning research group and Statistical Theory and Methodology at Oxford. Key contributions include advancing non-reversible parallel tempering techniques to enhance computational efficiency in high-dimensional sampling, with applications to astrophysics and statistical mechanics. His recent work emphasizes scalable algorithms and rigorous theoretical analysis of MCMC performance.

• Quantum Entanglement
• Photonics
• Quantum Information Science
• +۳ مورد دیگر

Natalia Herrera Valencia serves as a Research Associate at the Institute of Photonics and Quantum Sciences within Heriot-Watt University's School of Engineering & Physical Sciences. Her work centers on experimental quantum photonics, specifically manipulating high-dimensional quantum states for advanced information processing. Her research spans quantum entanglement engineering , photonic quantum computing , and noise-resilient quantum communication . Key specialties include structured light control, optical fiber networks for entanglement distribution, and tomographic reconstruction of complex quantum states. She investigates fundamental limits of quantum systems under losses and decoherence. Recent publications (2024-2025) reveal a concentrated effort in scalable quantum photonic architectures , with emphasis on multiplexed networks, inverse-designed optical circuits, and parallelized Bell tests. These works collectively advance high-dimensional quantum information protocols using integrated photonics platforms. Dr. Herrera Valencia actively collaborates with the quantum photonics group at Heriot-Watt, particularly within Mehul Malik's research team. Her experimental work leverages the university's state-of-the-art quantum optics facilities for generating and characterizing entangled photon states in complex media.

• VLSI Design
• AI/ML Processor Design
• Secure Computer Architecture
• +۳ مورد دیگر

Dr. Abbas A. Fairouz is an Assistant Professor in the Computer Engineering Department at Kuwait University. He holds a PhD from Texas A&M University (2019) and BS/MS degrees from Kuwait University (2006/2011). He previously served as a system engineer at Kuwait's Ministry of Electricity & Water (2006–2014) and as a part-time faculty member at PAAET's Higher Institute of Telecommunication and Navigation (2008–2010). Affiliations: Academic Visitor at University of Oxford (OSCAR Research Group) Research Focus: VLSI design, AI/ML processor architecture, secure computer systems, microarchitecture optimization, and FPGA-based acceleration. His current projects include hardware-based sorting networks, privacy-preserving instant messaging systems, and chiplet-based secure architectures. He has received the President of Kuwait Award (2012) and was a best paper nominee at GLSVLSI'17. His work spans hardware-software co-design for cryptographic accelerators, special function units (SFUs), and low-power NoC routers. Collaborations include the Oxford Secure Computer Architecture Research (OSCAR) group.

Qiang Guoمشاهده پروفایل

مدرس ارشد

• Formal Methods
• Software Engineering
• Distributed Systems
• +۵ مورد دیگر

Dr Qiang Guo is a Senior Lecturer in Computer Science at Teesside University, affiliated with the Department of Computing & Games within the School of Computing, Engineering and Digital Technologies. He holds a PhD in Computer Science from Brunel University London and has previously worked as a Research Associate/Fellow at the University of Sheffield, Robert Gordon University, and the University of Cambridge, as well as a Senior Software Engineer at MasterCard. PhD, Computer Science, Brunel University London (2023) Master, Computational Intelligence, University of Plymouth Bachelor, Industrial and Electrical Automation, Xi'an University of Architecture and Technology PGCert in Higher Education, Teesside University His research focuses on Formal Methods in Software Engineering , particularly model-checking and testing of Distributed and Concurrent Systems . He integrates Artificial Intelligence techniques into Software Conformance Testing and explores Algorithmic Skeleton-based Parallel Computing for software engineering applications. His work addresses verification challenges in Erlang/OTP systems, extended finite state machines, and timed components. Dr Guo’s publications highlight a trajectory in Formal Verification , Automated Testing , and Optimization Techniques . Key themes include the application of Genetic Algorithms to finite state machine testing, Process Algebra (μCRL/mCRL) for telecommunications systems, and Testability Transformations to improve structural coverage. Trends reflect interdisciplinary bridges between Software Engineering and AI . As a Principal Investigator (PI) for the Innovate UK-funded project MC-IoT: Model Checking IoT Systems (2024-25, £31,907), he leads research in IoT system verification. He also contributed as Co-Investigator (Co-I) to the Parrot AI Enterprise Project (2023, £40k). Dr Guo is affiliated with the Centre for Digital Innovation , where he contributes to advancing software engineering methodologies. His work involves collaboration with academic and industrial partners to address real-world challenges in system verification and distributed computing.

Rumyana Neykovaمشاهده پروفایل

مدرس ارشد

• Distributed Systems
• Formal Methods
• Concurrency Theory
• +۴ مورد دیگر

Dr. Rumyana Neykova is a Senior Lecturer in Computer Science at Brunel University London's College of Engineering, Design and Physical Sciences. She holds a PhD from Imperial College London and specializes in concurrency theory, distributed systems verification, and blockchain technologies. Her research employs formal methods, type systems, and model checking to enhance software reliability and prevent communication faults in distributed architectures. Research Focus: Her work spans distributed protocol verification, blockchain ecosystems (Ethereum, smart contracts), simulation validation, and software engineering education. Recent projects include developing fluid session types for end-to-end protocol verification and analyzing developer dynamics in blockchain communities. Teaching & Supervision: Dr. Neykova teaches undergraduate modules in Logic/Computation and Software Development, supervises final-year/MSc projects, and advises industry collaborations through Brunel Talent Marketplace. Grants: SEAVEA (EPSRC, 2021-2024): Software Environment for Actionable & VVUQ-evaluated Exascale Applications Fluid Session Types (UK Research Institute, 2019-2023): End-to-end verification of communication protocols Professional Activities: Regular peer reviewer for journals (e.g., Information and Software Technology ) and conferences (e.g., ACM SIGPLAN). Co-chaired workshops including PLACES and BlochArch.

Paul Richmondمشاهده پروفایل

استاد

• GPU Computing
• Agent-Based Modelling
• High-Performance Computing
• +۵ مورد دیگر

Paul Richmond is a Professor of Research Software Engineering at the University of Sheffield's School of Computer Science. He holds an EPSRC Early Career Research Software Engineering Fellowship focused on accelerating scientific discovery through GPU-accelerated architectures. With a strong interdisciplinary research track record, he develops software solutions for complex systems simulation using high-performance computing architectures. His research spans GPU computing, agent-based modeling, complex systems simulation, and high-performance computing methodologies. Richmond leads the development of FLAME GPU, a framework enabling large-scale agent-based simulations on GPUs, applied to domains including computational biology, transportation systems, and neural simulations. Analysis of his recent publications reveals strong emphasis on GPU-accelerated scientific computing, computational biology applications (particularly oncology and neuroblastoma modeling), transportation simulations, and parallel algorithm development. His work consistently bridges theoretical computer science with practical engineering applications. EPSRC Early Career Research Software Engineering Fellowship Fellow of the Higher Education Academy Richmond has secured substantial research funding including £4.3M as PI/CI over five years. Major grants include leadership roles in PRIMAGE (childhood cancer diagnostics), ExaTEPP (particle physics), and industrial collaborations with Fujitsu, Siemens, and Department for Transport. He founded and led the University of Sheffield's Research Software Engineering group, growing it to 13.5 FTEs supporting £13M in research projects. He established the GPUComputing@Sheffield group, leads the FLAME GPU development team, and served as Engineering Lead for Cambridge's Institute of Computing for Climate Science. Richmond is also former President of the Society for Research Software Engineering.

• Requirements Engineering
• Speech Emotion Recognition
• Cloud Computing
• +۳ مورد دیگر

Vito Veneziano is a researcher at the University of Hertfordshire , affiliated with the Department of Computer Science under the School of Physics, Engineering & Computer Science . His work spans multiple domains within computing, focusing on practical applications and theoretical analysis. Research Interests : Requirements Engineering and stakeholder dynamics Speech emotion recognition and deep learning Cloud computing algorithm optimization Usability analysis in software and ERP systems Interdisciplinary approaches to political context in engineering Human-computer interaction in gamified environments Recent Projects include AI-powered conversation trees for debt collection, metabolic disorder prediction using machine learning, and speech emotion recognition systems. Collaborations involve Manor Pharmacy Group, University of Hertfordshire colleagues, and industry partners.

Jonathan Woodruffمشاهده پروفایل

پژوهشگر ارشد

• Computer Architecture
• Security
• Programming Languages
• +۳ مورد دیگر

Dr. Jonathan Woodruff is a Senior Research Associate at the Department of Computer Science and Technology, University of Cambridge. His research focuses on secure computing architectures, with a particular emphasis on the CHERI (Capability Hardware Enhanced RISC Instructions) project. His work spans computer architecture, security, programming languages, and hardware-software co-design. Research Interests: Hardware-enhanced memory safety Secure processor architectures (RISC-V/CHERI) Formal verification of microarchitectures Compiler/runtime systems for secure execution Transient-execution attack mitigation Global address space security Recent work emphasizes validation of the Morello platform (ARM's CHERI implementation) and exploration of architectural contracts for safe speculation. His contributions include novel memory protection mechanisms and performance evaluation of secure architectures.

• Computer Architecture
• Machine Learning and Artificial Intelligence
• Embedded Systems
• +۴ مورد دیگر

Daniel Bates is a Senior Research Associate at the University of Cambridge's Department of Computer Science and Technology. His research focuses on Computer Architecture and Machine Learning, emphasizing co-optimization of hardware and software. Key projects include the Loki manycore processor (with 128 cores fabricated in 2018) and the Muntjac RISC-V multicore processor, designed for simplicity and extensibility. Bates explores energy-efficient machine learning optimizations like dynamic gating and network architecture search. He teaches courses including Part IA Algorithms, Part IB Computer Architecture, and Part II Advanced Computer Architecture. His supervision style prioritizes student feedback and clarity, offering tailored support and prompt communication. Bates has contributed to over a dozen peer-reviewed publications since 2013, addressing topics from neural network security to embedded system optimization. His work bridges theoretical research and practical hardware implementation, with a focus on open-source contributions like the Muntjac processor. He actively collaborates with industry through the University's research initiatives, emphasizing real-world applications of computer architecture advancements.

Robert Chatleyمشاهده پروفایل

استاد

• Software Engineering Education
• Serverless Computing
• Developer Experience
• +۳ مورد دیگر

Dr. Robert Chatley is a Professor and Director of the Software Engineering Practice group and DoC EdTech Lab at Imperial College London. He holds a PhD from Imperial and has extensive industry experience as a senior engineer and consultant before transitioning to academia. His work bridges industry and academia, focusing on improving software engineering education and developer productivity. Education: Completed his PhD at Imperial College London. His research emphasizes practical software engineering problems, particularly in education, serverless computing, and developer tooling. He leads initiatives to integrate DevOps practices into curricula and has published widely on topics like lean learning and agile methodologies. Research Interests: Software engineering education, serverless computing, developer experience, software testing, and programming languages. His work includes tools like PerfMock for performance testing and Diggit for automated code review, alongside frameworks like Nimbus for serverless applications. Articles highlight trends in education technology, serverless architectures, and developer tools. Collaborations include the Horizon 2020 RADON project and international workshops. He advises prospective PhD students interested in industry-relevant software engineering challenges. Labs/Teams: Leads the Software Engineering Practice group, focusing on industrial skills and tools. Collaborates with the Royal College of Art and global institutions. His consultancy, Develogical, extends his industry-academia bridge.

• Data center networking
• Optical circuit switching
• Distributed systems
• +۳ مورد دیگر

Paolo Costa is a Senior Principal Research Manager at Microsoft Research Cambridge and Honorary Lecturer at Imperial College London. His research bridges distributed systems and networking with focus on optical technologies for next-generation data centers. Key innovations include Sirius nanosecond optical switching architecture, soliton microcomb-based circuit switching, and PANAMA in-network aggregation for machine learning clusters. Research explores programmable switches, hardware acceleration, and AI infrastructure optimization. Projects include 'CamCube' and 'Predictable Datacenters' enhancing application-network integration. Recent publications examine memory systems for AI, stateful in-network computing, and lite-GPU clusters for scalable AI infrastructure.

Annabel Lathamمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence in Education
• Ethics and Trust of AI
• Computational Intelligence
• +۸ مورد دیگر

Dr. Annabel Latham is a Senior Lecturer in Computer Science at Manchester Metropolitan University within the Faculty of Science and Engineering’s Computing and Mathematics department. She holds a PhD in Artificial Intelligence, an MSc in Computing, a Postgraduate Certificate in Academic Practice, a CIM Diploma in Marketing, and a BSc(Hons) in Computation. As a Fellow of the Higher Education Academy (FHEA) and Senior Member of IEEE (SMIEEE), she contributes extensively to AI research and education. PhD in Artificial Intelligence MSc in Computing PGC Academic Practice CIM Diploma in Marketing BSc(Hons) Computation FHEA (2015) SMIEEE (2018) Research Interests include Artificial Intelligence in Education , Ethics of AI , and Computational Intelligence . She specializes in conversational agents, intelligent tutoring systems, and public trust in AI. Her work addresses fairness, accountability, and accessibility in AI-driven education, leveraging technologies like large language models and fuzzy logic. Research Outputs span 15 years, with a focus on explainable AI, educational applications of conversational agents, and ethical frameworks. Recent work (2024-2025) explores postdigital citizen science, trustworthy AI implementation, and XAI usability for non-specialists. 2023 IEEE Region 8 Outstanding Women in Engineering Volunteer Award 2019 IEEE Region 8 Outstanding Women in Engineering Affinity Group of the Year 2018 Outstanding Peer Reviewer, Elsevier: Computers & Education Senior Member IEEE (2018) FHEA (2015) Teaching and Supervision includes undergraduate Databases, postgraduate units in Information Systems and AI Ethics. She supervises MSc and PhD students in areas like explainability-aware machine learning, data responsibility, and AI trustworthiness. Her grants involve collaborations with international funding bodies such as NAFOSTED (Vietnam) and Croatia’s National Council for Science. Labs and Groups include the Computational Intelligence Lab, Machine Intelligence research group, and the Data and AI Ethics research group, where she co-leads initiatives on ethical AI in education.

• Distributed Systems
• Fault Tolerance
• Peer-to-Peer Networks
• +۳ مورد دیگر

Dr Stuart Norcross is a Scientific Officer and Researcher at the School of Computer Science, University of St Andrews. His work focuses on distributed systems, fault tolerance, peer-to-peer networks, and resilient middleware frameworks. He has contributed to projects funded by the Nuffield Foundation, including research on adaptable middleware for distributed applications and resilient web services infrastructure. His research emphasizes generative approaches to state machine design, Byzantine fault tolerance in distributed protocols, and innovative P2P architectures. Key areas of expertise include distributed algorithms, middleware design, and resilient service deployment. Recent work explores policy-aware frameworks separating application logic from distribution mechanisms, as well as adaptive garbage collection strategies for distributed systems. Norcross has authored/co-authored 16 research outputs including peer-reviewed conference papers and technical reports, with notable contributions to dependable systems architecture (e.g., Architecting Dependable Systems V ) and distributed application methodologies. His grants include the 2009 Nuffield Undergraduate Research Bursary and a 2007 project on policy-free middleware. Norcross collaborates extensively with colleagues like Prof. Alan Dearle and Dr. Geoffrey Kirby on foundational distributed systems research. He is based in the Jack Cole Building, contributing to both theoretical advancements and practical implementations in distributed computing.