Nikos Komninos is a researcher at City, University of London , specializing in cybersecurity, network security, and privacy-preserving systems. His work spans Internet of Things (IoT) , mobile ad hoc networks , and cloud computing security. Research Areas : Cybersecurity frameworks, machine learning for threat detection, quantum-resistant encryption, and privacy-preserving authentication systems. His recent publications focus on ransomware detection under concept drift, DDoS mitigation in IoT, and attribute-based encryption for fog computing. He has contributed to IEEE Transactions and journals like Computers & Security , with a trend toward real-time adaptive security systems and Bayesian risk assessment .
Maryam Imani is an Associate Professor of Water Systems Engineering at Anglia Ruskin University's School of Engineering and the Built Environment. As a Chartered Civil Engineer (CEng) and Fellow of the Higher Education Academy (FHEA), she specializes in water infrastructure resilience, sustainable drainage systems (SuDS), and computational modeling techniques. BEng (Hons) Civil Engineering, 2001 MEng Water Systems Engineering, 2006 PhD Water Systems Engineering, University of Exeter, 2012 PG Cert in Learning and Teaching in Higher Education, Anglia Ruskin University, 2016 Her research focuses on resilience modeling for water infrastructure, machine learning applications in water systems, and climate adaptation strategies . She leads projects addressing urban wastewater resilience, SuDS implementation in developing countries, and interdependent infrastructure systems. Maryam's work demonstrates a strong emphasis on multi-objective optimization and decision support systems for sustainable water management. Her recent publications explore challenges in Brazil, India, and the UK, integrating climate projections with urban planning. Exeter Research Scholarship (ERS) Fellow of the Higher Education Academy (FHEA) She contributes to major projects like Safe&SuRe water management and RESoURce@Brandia , securing grants from UKRI-GCRF, NERC, and EPSRC. Maryam collaborates with institutions across the UK, Brazil, and the US, including the University of Utah.
Professor Alan Penn is a leading academic at University College London's The Bartlett School of Architecture , where he holds the title of Professor in Architectural and Urban Computing. He previously served as Dean of the Bartlett Faculty of the Built Environment from 2009 to 2019 and has been instrumental in establishing Space Syntax Ltd , a UCL knowledge transfer spin-out company. His affiliations include membership in the Space Syntax Laboratory, board membership of UCL Consultants Ltd, and trustee status at Shakespeare North Trust. Education: BSc (1978), Dip Arch (1980), MSc (1983) - all from University College London Alan Penn’s research investigates how spatial design influences social and economic behaviors through innovative space syntax methodologies . Key areas include: Agent-based simulations of human behavior Spatio-temporal representations of built environments Urban spatial network analysis Urban sustainability across multiple dimensions Cognitive markers in architectural design Historical urban growth modeling His recent publications demonstrate a strong focus on computational urbanism, evolutionary city patterns, and behavioral architecture. Research trends show interdisciplinary approaches combining architectural theory with: Machine learning applications Network science analysis Behavioral psychology insights Historical GIS techniques Complex systems modeling Public health considerations Scientific recognition includes: HEFCE Business Fellowship (2001-2005) KTP SE Region Award (2010) Multiple UCL Enterprise awards ‘Spirit of Enterprise’ Award (2008) As Principal Investigator he leads the £5m EPSRC-funded Urban Dynamics Lab , demonstrating sustained research excellence. His work extends to public engagement through: Shakespeare North Trust educational theatre development Media appearances (New Scientist, Slashdot) Public policy contributions
Dr. Antoine Cully is the director of the Adaptive and Intelligent Robotics Lab at Imperial College London. He previously served as a Research Associate in the Personal Robotics Lab (2016–present) and earned his PhD in Robotics and Artificial Intelligence from UPMC (Paris), focusing on algorithms enabling robots to adapt to mechanical damage swiftly. His work has been internationally recognized, including a Nature cover publication and awards for his PhD thesis. His research interests span evolutionary robotics, stochastic optimization, and quality-diversity algorithms, with current projects involving the EU H2020 'PAL' initiative to develop adaptive robotics for user preferences. Education: M.Sc. in Intelligent Systems and Robotics (UPMC, 2012), Engineer degree in Robotics (Polytech-Paris UPMC, 2012), PhD in Robotics and AI (UPMC, 2015). Research emphasizes adaptive robotics, damage recovery, and autonomous learning. Notable contributions include the T-Resilience algorithm and MAP-Elites optimization framework. Awards include the 'Outstanding Paper 2015' and 'Best Thesis' accolades. His lab focuses on advancing AI-driven robotics for real-world applications.
Theodosia Stratoudaki is a Senior Lecturer in the Department of Electronic & Electrical Engineering at the University of Strathclyde, Faculty of Engineering. She joined the university in 2017 as a Strathclyde Chancellor’s Fellow and has since become a leading researcher in laser ultrasonics and remote sensing. She holds a PhD from the University of Warwick and completed postdoctoral research at the University of Cambridge and the University of Nottingham. Her research interests lie at the intersection of optics, acoustics, and materials engineering, focusing on laser-induced phased arrays (LIPAs) for remote ultrasonic imaging, non-destructive evaluation (NDE), and in-process monitoring in extreme environments. She applies these techniques to advanced manufacturing, including additive manufacturing and nuclear applications, collaborating with industrial partners such as the UK Atomic Energy Authority, Sellafield, and Hitachi. The trends in her recent publications show a strong emphasis on improving the resolution, efficiency, and adaptability of laser ultrasound systems—particularly through innovations in array design, grating lobe suppression, signal processing, and machine learning integration. Her work increasingly incorporates robotics and deep learning for automated inspection and tomography. She has received multiple scientific awards, including: EPSRC DTA PhD studentship (2018) BINDT Annual Conference Paper Award (2018) Best Paper Award (2018) Best Paper Award (2015) Dr. Stratoudaki is actively involved in research leadership and mentoring. She is currently recruiting PhD students and supervising multiple funded projects, such as the Robotic Laser Ultrasonic Inspection System and Impact Enhancement for Adaptive Laser Induced Phased Arrays (ALIPA). She also contributes to professional service as co-chair of the departmental Equality, Diversity and Inclusion (EDI) committee, chair of the Institute of Physics’ Physical Acoustics group, and a member of the British Standards Institute’s ultrasonics committee (EPL/87). She leads a research team focused on laser ultrasonics and is part of collaborative networks involving the University of Strathclyde’s Centre for Ultrasonic Engineering and industrial partners. Her lab develops advanced optical systems for non-contact ultrasonic inspection, often integrating robotics and AI for real-time, in-process evaluation.
Professor Geoffrey Barton is the Chair of Bioinformatics at the Computational Biology department within the School of Life Sciences at the University of Dundee . With a career spanning decades, he has been pivotal in advancing bioinformatics tools and methodologies for analyzing biological data, particularly in protein structure prediction and RNA sequencing. Core Research Interests : Protein structure and function prediction, computational methods for large biological datasets, small RNA analysis, and integration with wet-lab collaborations across plants, model organisms, and human disease. Awards : Fellow of the Royal Society of Edinburgh (2019) Fellow of the Royal Society of Biology (2011) Brian Cox Prize for Excellence in Public Engagement with Research (2023) Publications and Software : He leads the development of widely used tools like JPred (25,000+ predictions/month) and Jalview (55,000+ installations). His group's work spans proteomics, transcriptomics, and structural genomics, addressing questions in basic science and clinical applications. Media and Collaboration : Available for media commentary on bioinformatics and computational biology, he collaborates extensively with international institutions, including the University of Cambridge and Oxford.
Dr David Walker is a Senior Lecturer in Computer Science at the University of Exeter and a member of the Institute for Data Science and Artificial Intelligence . He also contributes to the Environmental Intelligence @Exeter research network. Education: PhD in Computer Science, University of Exeter (2008–2013) BSc (Hons) in Computer Science, University of Exeter (2004–2007) Research Interests Dr Walker’s work sits at the intersection of multi-objective optimisation , evolutionary computation , explainable AI and hyper-heuristics . He develops algorithms and visual analytics that help engineers and scientists understand complex optimisation landscapes, with recent emphasis on renewable-energy planning (especially offshore wind farms) and trustworthy AI systems. Publication Trends Between 2022 and 2025 he produced a prolific stream of articles on explainable optimisation , many-objective wind-farm design and visual analytics for evolutionary algorithms . These works combine rigorous algorithmic innovation with real-world case studies, demonstrating a clear trajectory toward transparent, human-centred AI for engineering decision-making. Scientific Awards No specific awards or fellowships are mentioned in the provided material. Advising & Funding No explicit list of PhD students, post-docs or grant awards is supplied. Laboratory & Teams Dr Walker is affiliated with the Institute for Data Science and Artificial Intelligence and the Environmental Intelligence @Exeter network, indicating collaborative, interdisciplinary research environments.
Professor Eduardo Alonso is Director of the Artificial Intelligence Research Centre (CitAI) and Department Research Director at City St George's, University of London. His research bridges novel AI techniques with Explainable AI and Artificial General Intelligence, with significant focus on legal and ethical implications. Research spans: Computational neuroscience and evolutionary biology modeling Deep learning architectures for reinforcement learning Mathematical models of emergence in complex systems Industrial AI applications with societal impact Professor Alonso has secured over £1M in funding from Innovate UK, EU EIT-Digital, and US NSF grants. He currently supervises 13 PhD students working on ethical AI, reinforcement learning, and cybersecurity. Recent publications focus on transformer architectures for multi-agent systems, power grid optimization via GNNs, and adversarial robustness in security systems. Awarded the IEEE Computational Intelligence Society Spotlight Paper Award in 2013.
Dr. Wei Sun is a Chancellor's Fellow (equivalent to Assistant Professor) in Energy Systems Integration at the University of Edinburgh's School of Engineering. His research specializes in low-carbon energy systems with high renewable penetration, utilizing data science and optimization techniques. He contributes to major initiatives like the National Centre for Energy Systems Integration (CESI) and Hydrogen’s Value in Energy Systems (HYVE). Research encompasses network integration of distributed energy resources, climate impacts on renewables, and multi-vector energy systems. Recent publications focus on hybrid energy storage, hydrogen integration, and machine learning applications for system optimization. He holds professional credentials as a Chartered Engineer (CEng) with memberships in IET and IEEE. Teaching includes Hydropower Design Projects and Renewable Energy Fundamentals. Visiting research affiliations include University College London, enhancing collaborative networks in energy systems research.
Dr Alexis Kirke is a Senior Research Fellow in Computer Music at the School of Art, Design and Architecture (Faculty of Arts, Humanities and Business) at the University of Plymouth. As a composer-in-residence, he specializes in interdisciplinary research at the intersection of music, computing, and healthcare. His work includes developing adaptive music systems like RadioMe for dementia care, applying quantum computing to music composition, and exploring affective computing through brain-computer interfaces. Teaching roles include associate lecturer positions in modules such as Collaborative Practice (BA Sound and Music Production), Psychology (BA Music), and MRes Computer Music. He has supervised five PhD students as a second supervisor and served as an internal PhD examiner. His research focuses on algorithmic composition, music technology for healthcare, quantum computing applications in music, and multi-agent systems inspired by natural phenomena like humpback whale song evolution. Recent projects include the Plymouth Marine Institute collaboration and the Cloud Chamber performance involving real-time interaction with subatomic particles. Key contributions include innovative systems like RadioMe, which combines adaptive radio with reminder systems for dementia patients, and Q-Muse, a quantum computer music system. His work bridges computational creativity with human-centric applications, emphasizing ethical and accessible technology. Grants & Awards: No specific awards listed, but active in collaborative research projects Lab/Teams: Plymouth Marine Institute, Cloud Chamber Project
Professor Paul Stewart is affiliated with the University of Derby's College of Science and Engineering, specializing in Control and Systems Engineering. His research focuses on biomedical monitoring systems, nuclear reactor optimization, airport operations, and aerospace propulsion. Notable projects include developing real-time blood pressure estimation systems for dialysis patients and advancing modular nuclear reactor designs using genetic algorithms. He collaborates across disciplines, addressing challenges in energy efficiency, control systems, and transportation logistics. His work integrates advanced algorithms and engineering principles to solve complex problems in healthcare, aerospace, and sustainable energy. Research interests span hemodialysis monitoring technologies, genetic algorithm applications in modular systems, and multi-objective optimization for airport ground movements. His contributions also include pioneering studies on solar-powered high-altitude aircraft and energy-efficient electric propulsion systems. Despite no explicitly listed awards or grants, his prolific publications reflect sustained academic and industrial engagement. Key collaborations involve institutions like the University of Derby and international teams in nephrology, aerospace, and transportation engineering fields. While no labs or formal research teams are named, his work indicates involvement in interdisciplinary research networks focused on practical engineering solutions with societal impact.
Min Chen is a Professor of Scientific Visualization at the University of Oxford, affiliated with the Department of Engineering Science and Pembroke College. He holds fellowships from the British Computer Society, European Computer Graphics Association, and Learned Society of Wales. His career spans over three decades, with previous roles at Swansea University (1984–2011) and current leadership in visualization research. His research focuses on visualization theory, video visualization, visual analytics, and interdisciplinary applications in fields like epidemiology and cybersecurity. He has authored over 200 publications and led projects such as RAMPVIS during the COVID-19 pandemic. Key roles include editor-in-chief of Computer Graphics Forum and associate editor of IEEE Transactions on Visualization and Computer Graphics. Education: BSc and PhD in relevant fields (details not explicitly stated in texts). Awards include the VGTC Visualization Lifetime Achievement Award (2024). His work emphasizes the theoretical underpinnings of visualization and practical tools for data intelligence.
Roles and Affiliations: Sukhpal Singh Gill is a Lecturer (Assistant Professor) in Cloud Computing at Queen Mary University of London (QMUL), UK. He leads the GillNet Research Lab and is the Editor-in-Chief of the International Journal of Applied Evolutionary Computation (IJAEC) . He also serves as an Associate Editor for journals like IEEE IoT and Nature Scientific Reports. As Programme Director for MSc Advanced Computer Science and MSc Business Analytics, he contributes to curriculum development and education excellence. Research Interests: His research focuses on Cloud Computing, Edge AI, Internet of Things (IoT), and Energy Efficiency. He explores AI-driven solutions for resource management, security, and sustainable computing. Key areas include fog-edge integration, serverless computing frameworks, and healthcare applications. Publications and Impact: With over 200 peer-reviewed publications (including IEEE TCC, Elsevier JSS, and ACM TOIT), Dr. Gill has achieved 12,500+ citations and an H-index of 54 (Google Scholar). His work has been featured in IEEE Spectrum and Tech Monitor. Notable contributions include frameworks like HealthEdgeAI (healthcare systems), CloudAISim (cloud simulation), and EdgeAISim (edge computing modeling). Awards and Recognition: Recognized with the 2024 IEEE Outstanding Reviewer Award, Elsevier Editor’s Choice Award, and Queen Mary Education Excellence Award. He is a Fellow of the Higher Education Academy (FHEA). Teaching and Leadership: Teaches modules like Cloud Computing (Postgraduate) and Semi-structured Data Modeling. Leads the Networks and Systems Teaching Group (N&STG) and chairs academic misconduct panels. Advocates for inclusive curriculum design and intercultural development in higher education. Labs and Collaborations: The GillNet Lab develops next-generation systems for EdgeAI, CloudAIBus, and CloudAISim. Collaborates with institutions like Lancaster University, The University of Melbourne, and industry partners on fog-cloud IoT ecosystems.
Dr. Wanpeng Li is a Lecturer in Cyber Security within the Department of Computer Science at the University of Liverpool. Prior to this role, he held lecturer positions at the University of Aberdeen and Manchester Metropolitan University, and worked as a postdoctoral researcher at City, University of London. His research focuses on critical areas in cyber security including web security, identity management, authentication mechanisms, and malware detection using machine learning. Research Trends: His recent publications span both cyber security and mathematical modeling domains. Key security themes include automated vulnerability detection, federated learning attacks, and privacy-preserving protocols for vehicular networks and IIoT systems. Parallel studies in grey system models explore energy consumption forecasting and environmental impact analysis using fractional calculus and neural network integrations. Advising: Dr. Li actively accepts PhD students in cyber security-related fields.
Leni Le Goff is a Lecturer at the School of Computing, Engineering and the Built Environment , Edinburgh Napier University. Her research bridges robotics , evolutionary computation , and environmental sustainability . Key research interests include: Evolutionary design of robot morphologies and controllers Integration of individual and cultural learning in artificial evolution Application of autonomous systems for terrestrial biodiversity monitoring Optimization frameworks for robotic policy search Manufacturability constraints in morpho-evolution Transdisciplinary collaboration between ecologists and roboticists Recent publications highlight her work on: Developing generalized early stopping criteria for policy search Mapping fitness landscapes in morpho-evolution Assessing robotic solutions for ecological surveying Overcoming hierarchical optimization challenges in coevolution Creating biodegradable and deployable robotic systems Evaluating manufacturability trade-offs in evolved robot designs Active in the Autonomous Robot Evolution (ARE) project, she collaborates with leading researchers like Prof Emma Hart and Prof Karen Diele. Her work receives funding from EPSRC and the Carnegie Trust , focusing on real-world deployment challenges and computational efficiency improvements.
