جست‌وجوی استاد و پژوهشگر

Michalis Matthaiouمشاهده پروفایل

استاد

• Wireless Communications
• Signal Processing
• Massive MIMO
• +۳ مورد دیگر

Michalis Matthaiou is a Professor of Communications Engineering and Signal Processing at Queen’s University Belfast (QUB), UK, and Deputy Director of the Centre for Wireless Innovation (CWI). He holds a Diploma in Electrical and Computer Engineering from Aristotle University of Thessaloniki (2004), an M.Sc. (Distinction) from the University of Bristol (2005), and a Ph.D. from the University of Edinburgh (2008). Prior roles include Assistant Professor at Chalmers University of Technology (Sweden) and postdoctoral research at TU Munich (Germany). His research focuses on signal processing for wireless communications, massive MIMO, intelligent reflecting surfaces, and AI-driven systems. He leads a team of 20 researchers under multi-million-pound grants, including the ERC Consolidator Grant BEATRICE (2021–2026). **Affiliations**: Centre for Wireless Innovation, Institute of Electronics, Communications & Information Technology **Awards**: IEEE Fellow (2023), Leonard G. Abraham Prize (2017), EURASIP Early Career Award (2019) His work spans over 340 publications (140+ journal papers) and includes groundbreaking contributions to wireless systems. He supervises PhD students in areas like edge computing, reconfigurable intelligent surfaces, and millimeter-wave systems. He serves as Editor-in-Chief of Elsevier’s Physical Communication and Senior Editor for IEEE journals.

• Computational Fluid Dynamics (CFD)
• Turbulent Combustion
• High Performance Computing (HPC)
• +۵ مورد دیگر

Professor Karl Jenkins is a Professor of Computational Engineering at Cranfield University , where he leads the Centre for Computational Engineering Sciences . His expertise spans Computational Fluid Dynamics (CFD) , Turbulent Combustion , High Performance Computing (HPC) , and Multiphase Flow Modeling . Jenkins has published over 100 papers and received the Gaydon Prize for his contributions to combustion research. His research focuses on reacting flows , turbulence modeling , and compressible multiphase flows , with recent work addressing green hydrogen production , aircraft component segmentation , and virtual reality applications in aviation safety. He has developed high-order numerical methods for shock wave analysis and interface-capturing in unstructured mesh environments . A former Sir Arthur Marshall Research Fellow at Cambridge University, Jenkins combines academic rigor with industrial collaboration , having worked with companies like Rolls-Royce plc , Airbus SE , and Siemens AG . He mentors research students including Yiren Tong and actively contributes to LES/DNS computational frameworks for aerospace and environmental applications .

• Rheumatoid Arthritis
• Inflammatory Arthritis
• Genetics
• +۷ مورد دیگر

Dr. Darren Plant is a Senior Lecturer in the Division of Musculoskeletal & Dermatological Sciences within the School of Biological Sciences at the University of Manchester. His research focuses on identifying genetic and genomic factors that underpin response to therapy and comorbidity risk in rheumatic diseases, particularly rheumatoid arthritis. His research interests span rheumatoid arthritis, inflammatory arthritis, genetics, genomics, pharmacogenomics, TNF inhibitors, treatment response prediction, and comorbidity risk. His work integrates cutting-edge genomic approaches with clinical data to understand why patients respond differently to treatments. He has made significant contributions to understanding the genetic basis of treatment response in rheumatoid arthritis, particularly regarding TNF inhibitors and other biologic therapies. Analysis of Dr. Plant's recent publications reveals a strong focus on biomarker discovery using multi-omics approaches (genomics, transcriptomics, metabolomics) to predict treatment response in rheumatoid arthritis. His work increasingly incorporates machine learning techniques to analyze complex biological data. A notable trend is his investigation into the relationship between socioeconomic factors and treatment outcomes, highlighting the intersection of biological and social determinants of health in rheumatic diseases. Dr. Plant has supervised multiple research projects, with evidence of 4 supervised works according to his institutional profile. His research is supported by collaborations across the University of Manchester and with international partners, as evidenced by his extensive co-authorship network. His laboratory work focuses on analyzing genetic, genomic, and proteomic data from rheumatoid arthritis patients to identify predictors of treatment response and disease progression. His team employs advanced statistical and computational methods to integrate multi-omics data with clinical outcomes.

• Computational Fluid Dynamics (CFD)
• Turbulence Simulation
• Wind Farm Optimization
• +۵ مورد دیگر

Professor Sylvain Laizet is a faculty member in the Department of Aeronautics at Imperial College London, part of the Faculty of Engineering. He holds a PhD and Habilitation à Diriger des Recherches from the University of Poitiers in France, specializing in Computational Fluid Dynamics (CFD). His research focuses on turbulent flows and their engineering applications, including wind farm optimization, quantum algorithms for fluid mechanics, and machine learning integration in CFD. Key research areas include: Wake-to-wake interaction in wind farms Bayesian optimization for drag reduction and energy efficiency Immersed boundary methods for moving objects Quantum computing for solving PDEs in fluid dynamics His work leverages high-order numerical methods and large-scale simulations, with contributions to frameworks like Xcompact3D and WInc3D. Recent publications emphasize quantum algorithms, turbulence entrainment, and data-driven optimization strategies for renewable energy systems. Scientific contributions span over 50 peer-reviewed articles in top-tier journals, focusing on advancing CFD methodologies and their applications in environmental and industrial fluid mechanics. His team collaborates globally, including partnerships in France and Brazil.

• Materials Modelling
• Micro-mechanics
• Voronoi Tessellation
• +۱ مورد دیگر

Dr. Pan Zhang is a Researcher at the Department of Mechanical Engineering, Imperial College London, specializing in materials modeling and micro-mechanics. His work focuses on crystal plasticity modeling, particularly the generation of microstructures for polycrystalline materials to support finite element analysis. He holds a BSc and MSc in Control Engineering and a PhD in Mechanical Engineering. Research interests include Voronoi tessellation applications, optimization using evolutionary algorithms, and material behavior under extreme conditions. His contributions span computational geometry, composite materials, and supply chain environmental impact analysis. Publications highlight advancements in grain structure simulation, cryptographic integration in embedded systems, and cloud-based privacy-preserving techniques. Collaborations include projects with Professors Liliang Wang and Daniel Balint, though he is not directly listed as a supervisor for the mentioned PhD studentships. No scientific awards are explicitly stated, but his work demonstrates expertise in interdisciplinary engineering and computational methods.

Sid-Ali Amamraمشاهده پروفایل

مدرس ارشد

• Power Electronics
• Electric Vehicles Integration
• Electric Machines and Drives
• +۳ مورد دیگر

Dr. Sid-Ali Amamra is a Senior Lecturer in Electrical Engineering at the School of Computing and Engineering, University of Huddersfield. His research focuses on power electronics, electric vehicles integration, smart grid technologies, and renewable energy systems. Education: PhD in Electrical Engineering/Power Electronics from the University of Versailles Saint-Quentin-En-Yvelines (UVSQ) in 2013 Research Expertise Dr. Amamra's work centers on power electronics and electric vehicle integration , with emphasis on smart grid systems , renewable energy , and energy storage . His research contributes to UN Sustainable Development Goals (SDGs) through innovations in energy efficiency and sustainable transportation. Recent Research Trends Current publications highlight: blockchain energy trading for EVs (2025), machine learning for battery health prediction (2025), and multilevel inverter topologies for grid integration (2025). Earlier works focus on microgrid control strategies, harmonic distortion mitigation, and advanced EV charging systems. Activities Editorial work for Sustainability journal (2022-2023) Oral presentation on PEV scheduling in industrial microgrids (2019)

Ilias Tachmazidisمشاهده پروفایل

مدرس ارشد

• Knowledge Representation and Reasoning
• Semantic Web
• Artificial Intelligence in Medicine
• +۳ مورد دیگر

Ilias Tachmazidis is a Senior Lecturer in the Department of Computer Science at the University of Huddersfield's School of Computing and Engineering. He actively contributes to research within the Centre for Autonomous and Intelligent Systems and the Centre of Artificial Intelligence for Mental Health. His academic journey includes a PhD from the University of Huddersfield (2015) and previous research roles in the PARK group. Education: University of Crete (B.Sc. 2010, M.Sc. 2012) Current academic rank: Senior Lecturer Active research centers: Centre for Autonomous and Intelligent Systems, Centre of Artificial Intelligence for Mental Health His research spans foundational AI concepts and applied implementations, with specific emphasis on: Knowledge Representation and Reasoning Semantic Web Technologies High Performance and Distributed Computing Artificial Intelligence Applications in Medicine and Law Recent publications highlight his work at the intersection of large language models and formal verification, alongside practical implementations for ADHD diagnosis using AI. The research demonstrates consistent engagement with UN Sustainable Development Goals through technology solutions that balance scientific rigor with societal impact. While not explicitly listing scientific awards, his activities show substantial contributions through peer-review work at IEEE conferences (2016-2020) and collaborative projects like MIREL (MIning and REasoning with Legal texts) that produced notable outputs in regulatory compliance systems.

Francois Sieweمشاهده پروفایل

عضو هیئت علمی

• Computer Security
• Pervasive Systems
• Formal Methods
• +۶ مورد دیگر

Francois Siewe is a Reader in Computer Science at De Montfort University (DMU), affiliated with the School of Computer Science and Informatics within the Faculty of Computing, Engineering and Media. He conducts research in the Software Technology Research Laboratory (STRL) and the Cyber Technology Institute (CTI). His work spans formal methods, pervasive systems, and cybersecurity. His research interests include: Computer Security Pervasive Systems Formal Methods Process Calculi Formal Verification The recent publications highlight a strong trend in applying formal techniques to software modeling and verification, integrating AI for health and environmental monitoring, and advancing software quality assessment. His work often bridges theoretical foundations with practical system design, particularly in context-aware and distributed environments. Scientific awards: Research Journal of Textile and Apparel (RJTA) Excellent Paper Award 2011 Francois Siewe actively supervises postgraduate research. He is first supervisor for Ahmed Mohammed Alalshuhai, Abdulgader Zaid Almutairi, Saud Maqed Almutairi, Muslit Awadh Alotaibi, Asma Abdulghani Qasem Al-Shargabi, Elena Chernikova, and Abdulghani Mahmoud Suwan. He serves as second supervisor for Abdullah Shawan Alotaibi and Amr Mohsen Jadi. While specific grants are not listed, his past involvement in EPSRC-funded projects (e.g., MELANGE) indicates experience with competitive research funding. He is a key member of the Software Technology Research Laboratory (STRL), contributing to its focus on software engineering, cybersecurity, and ambient intelligence.

Maria Jenisha Charles Thanasingh Packiarajمشاهده پروفایل

مدرس

• Renewable Energy Systems
• Power Electronics
• Smart Grids
• +۱۱ مورد دیگر

Maria Jenisha Charles Thanasingh Packiaraj is a Lecturer in Electrical Engineering at the School of Computing, Engineering and Digital Technologies, Teesside University, UK, where she has been serving since October 2022. She leads the Electrical Power Systems module at Level 6 and tutors in Electronic Principles and Microgrid courses, while also supervising undergraduate and postgraduate dissertation projects. Post Graduate Certificate in Learning and Teaching in Higher Education (PgCLTHE), Teesside University (Awarded: 29 Aug 2024) PhD in Power Electronics Applications in Renewable Energy Systems, National Institute of Technology Tiruchirappalli (Awarded: 24 Aug 2019) Master of Engineering in Power Electronics and Drives, Infant Jesus College of Engineering, India (Awarded: 31 May 2014) Bachelor of Engineering in Electrical and Electronics Engineering, PSG College of Technology, India (Awarded: 31 May 2012) Her research spans renewable energy integration , power electronics , microgrids , smart grids , energy storage , and electric vehicle charging . She focuses on advanced control techniques like Fuzzy-PID controllers , unintentional islanding detection , and AI-driven battery management , contributing to sustainable and resilient energy systems. The recent publications highlight a strong trend in grid-connected renewable systems , islanding detection without communication , offshore wind turbine control , and AI-enhanced charging technologies . These works reflect expertise in both theoretical modeling and practical implementation, particularly in power conversion, control algorithms, and system resilience. Dr. Charles Thanasingh Packiaraj is actively involved in research funding and supervision. She serves as Co-Investigator on the Royal Academy of Engineering-funded project AI-Driven Adaptive Fast Charging for Electrical Vehicles – Empowering Skills and Curriculum Development , which also emphasizes education and workforce development. She is open to PhD supervision and collaborative research projects in her domain. Her research contributes to key themes in modern power systems, including decentralized energy , smart control , and sustainable electrification . She collaborates with researchers in power electronics, renewable integration, and intelligent transportation systems, forming part of a dynamic network advancing clean energy technologies.

Peter Popovمشاهده پروفایل

پژوهشگر

• Software Reliability
• System Dependability
• Software Fault-Tolerance
• +۵ مورد دیگر

Peter Popov is a Reader at the Centre for Software Reliability (CSR) , City St George's, University of London , where he has been employed since 1997. He specializes in software dependability , fault tolerance , and stochastic modeling of critical infrastructures. Before his current position, he was an Associate Professor at the Bulgarian Academy of Sciences (1990-1997) and a Research Fellow at City St George's. Peter's academic journey began with a PhD in Computer Science from the Kiev National University of Technologies and Design (1989), following his BEng in Computer Engineering from the National Technical University of Ukraine (KPI, 1982). He has worked as a visiting scientist at renowned institutions including the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign , LAAS-CNRS in Toulouse, and Duke University . His research interests span Software reliability assessment System dependability Software fault-tolerance Performance evaluation Interdependencies of critical infrastructures He has contributed extensively to projects such as ReSIST , IRRIIS , DISPO , and AFTER , focusing on the dependability of composite systems and critical infrastructure resilience. Key publication trends reveal expertise in Stochastic modeling of autonomous vehicle safety Software diversity for fault tolerance Interdependency analysis in critical systems Bayesian reliability assessment Performance evaluation of distributed protocols Security implications in cyber-physical systems Peter has supervised several PhD students , including those researching autonomous vehicle resilience , safety assurance with ML components , and adaptable web services . His professional activities include serving on program committees for ISSRE , SAFECOMP , and EDCC conferences, as well as editorial contributions to CEUR Workshop Proceedings . He is proficient in Bulgarian , English , and Russian , with peer-review capabilities in all three languages.

• Algorithmic Graph Theory
• Combinatorial Optimization
• Graph Colouring
• +۷ مورد دیگر

Professor Rhydian Lewis is a distinguished academic at Cardiff University's School of Mathematics, holding a Personal Chair since 2023. Previously, he served as a Reader (2019-2023), Senior Lecturer (2015-2019), and Lecturer (2008-2015) at the same institution, with earlier appointments at Cardiff Business School (2006-2008) and Edinburgh Napier University (2003-2006). He is a Fellow of the Higher Education Academy and serves as an Associate Editor for the International Journal of Metaheuristics. His research spans algorithmic graph theory, combinatorial optimization, and operational research, with specific expertise in graph coloring, vehicle routing, shortest path algorithms, school bus routing, automated timetabling, and metaheuristics. Lewis has made significant contributions to both theoretical and applied aspects of these fields, developing practical solutions for real-world problems in transportation, agriculture, healthcare scheduling, and network analysis. His recent publications demonstrate a strong trajectory in graph theory applications, particularly in street network analysis, payment channel networks, and livestock routing. The research shows increasing interdisciplinary connections between theoretical computer science, operations research, and practical applications in urban planning, financial technology, and agricultural engineering. His work often bridges theoretical algorithm development with practical implementation, as evidenced by his GCol Python library for graph coloring. Fellow of the Higher Education Academy Associate Editor, International Journal of Metaheuristics Guest Editor, Special Issue on Algorithms for Graphs and Networks (Algorithms, 2020) Program Committee Member for EVOCOP, PATAT, and GECCO conferences Professor Lewis actively supervises PhD students in combinatorial optimization, algorithmic graph theory, and transportation problems. His current supervisees include Monique Sciortino, Daniel Hambly, and Lukas Dijkstra, while his past students have completed research on score-constrained packing, dynamic graph coloring, dynamic arc routing, urban transportation networks, operating theatre schedules, and vehicle routing problems. His collaborative work spans multiple institutions and disciplines, particularly with researchers like P. Corcoran, J. Thompson, and D. Thiruvady. Lewis maintains active research teams focused on graph algorithms and operational research applications, with strong connections to industry through projects like the European Consortium for Mathematics in Industry. His work on school transport systems demonstrates practical impact in community applications.

Bernd Behrمشاهده پروفایل

مدرس ارشد

• Photography
• Moving Image Art
• Architectural Art Practice
• +۷ مورد دیگر

Bernd Behr is a Senior Lecturer in Photography at Camberwell College of Arts, University of the Arts London. He has previously taught at the University of Gloucestershire and Goldsmiths, University of London. His practice combines moving image, photography, sculpture, and writing, with a focus on intersections between historical narratives, architectural sites, and visual culture. Education: San Jose State University, California; Goldsmiths, University of London Residencies: Akademie Schloss Solitude (Germany), Makan/Triangle Arts Trust (Jordan) Behr's research explores photographic indexicality, machine vision, and the built environment. His projects often use speculative methodologies to examine material and narrative provenance in imaging systems, particularly through collaborations with engineering institutions and archaeological practices. Recent work investigates autonomous vehicle vision systems, blockchain-based image economies, and taxidermic imaging techniques. His publications and presentations analyze visual cultures across historical and technological contexts. Awards: Beck's Futures 2003, Artsadmin deciBel Award 2006 Grants: Film London funding, Arts Council England Behr maintains active collaborations across art-science fields and contributes to editorial work at the Philosophy of Photography journal.

Martin Reedمشاهده پروفایل

استاد

• Computer Networking
• Network Security
• Internet of Things Security
• +۵ مورد دیگر

Professor Martin Reed is a Professor and Deputy Head of the School of Computer Science and Electronic Engineering at the University of Essex. His academic career spans over two decades, with significant contributions to computer networking and network security research. He has played a key leadership role in curriculum development for the school, merging the curricula of two former departments into the current structure. Martin Reed earned his PhD from the University of Essex in 1997 and completed his BEng (1st Class) with an Industrial Year at BBC Research Department from the University of Surrey in 1989. His educational background provided a strong foundation for his subsequent research career in networking technologies. Professor Reed's research focuses on computer networking and network security, with particular emphasis on Internet of Things security, Software Defined Networking (SDN) security, Information Centric Networking, and multimedia transmission over networks. His work bridges theoretical research with practical applications, addressing real-world challenges in network infrastructure. He has supervised numerous PhD students who have gone on to contribute to these fields, and his research has evolved to address emerging challenges in networked systems as technology has advanced. Analysis of Professor Reed's recent publications reveals a strong focus on applying artificial intelligence and machine learning techniques to network security challenges, particularly in the context of Software Defined Networking and Internet of Things environments. His work demonstrates a progression from traditional network security approaches to more sophisticated, AI-driven solutions that can adapt to evolving threats. There's also a clear trend toward addressing security challenges in distributed and edge computing environments, reflecting the changing landscape of networked systems. Professor Reed has successfully secured funding from multiple prestigious sources including the European Commission, Innovate UK, and British Telecommunications. His grants portfolio demonstrates his ability to translate theoretical research into practical applications with industry relevance. He has led projects focused on network security, information-centric networking, and IoT security, often collaborating with industry partners to ensure real-world applicability of research outcomes. As an academic supervisor, Professor Reed has guided numerous PhD students through their research journeys, with recent completions focusing on topics like IoT security, SDN security, and information-centric networking. His supervision record spans over a decade, showing consistent engagement with emerging research areas as the field has evolved. He also serves as an external examiner for undergraduate and postgraduate programs at multiple UK universities, contributing to academic quality assurance across the sector.

Hussain Ali Abidمشاهده پروفایل

پژوهشگر

• Computational Fluid Dynamics
• Computational Aeroacoustics
• Machine Learning
• +۳ مورد دیگر

Dr. Hussain Ali Abid is a Postdoctoral Research Assistant at the School of Engineering and Materials Science, Queen Mary University of London. His research focuses on computational fluid dynamics, aeroacoustics, and machine learning applications in aerospace engineering. BEng(Hons), PhD Research Interests: Computational aeroacoustics Large-eddy simulations Jet and propeller noise modelling Machine learning in aerodynamics Trailing edge noise prediction Analytical and GPU-accelerated methods Publications highlight his work on CABARET method applications, chevron nozzle noise reduction, and data-driven noise models. He specializes in rotating mesh simulations and turbulent flow anisotropy studies.

• Cryptography
• Secure Multi-Party Computation
• Blockchain
• +۳ مورد دیگر

Dr Aydin Abadi is a Research Fellow at Newcastle University specializing in cryptography and security systems. His research spans privacy-preserving technologies, blockchain architectures, and secure multi-party computation protocols, with active publication output from 2015 through 2025. His primary research domains include Cryptography, Secure Multi-Party Computation (particularly Private Set Intersection variants), Blockchain Applications, Privacy-Preserving Computation, Distributed Systems Security, and Federated Learning. He has pioneered protocols for verifiable delegated computation on outsourced datasets and developed novel approaches to Byzantine fault tolerance in distributed ledgers. Analysis of his 9 publications (2015-2025) reveals an evolutionary trajectory from foundational cryptographic protocols (2015-2019) toward applied blockchain systems and machine learning security (2023-2025). His recent work integrates cryptographic techniques with federated learning frameworks and develops commercial-grade blockchain alternatives, demonstrating consistent innovation in bridging theoretical cryptography with real-world system implementations.