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Professor David Andrews is Professor of Engineering Design in the Department of Mechanical Engineering at University College London (UCL). A globally recognised authority on naval architecture and ship design methodology, he has held continuous academic appointments at UCL since 1980, punctuated by distinguished service in the UK Ministry of Defence where he rose to Director of Frigates and Mine Countermeasures. Since 2000 he has occupied the Chair in Engineering Design at UCL, leading major research initiatives funded by EPSRC, ONR and the EU, and forging strategic industrial partnerships. Education Bachelor of Engineering, UCL (1970) MSc Naval Architecture, UCL (1971) PhD “Synthesis in Ship Design”, UCL (1984) Research Focus Professor Andrews is acknowledged as the world-leading expert in naval ship design methodology, with seminal contributions to early-stage design processes, submarine architecture, trimaran/multi-hull vessels, and distributed ship service systems. His pioneering Design Building Block approach and SURFCON CAD tool have been integrated into industry-standard platforms such as PARAMARINE. Current work addresses energy balance frameworks, computer-aided sketching, and philosophical foundations of engineering design. Across more than 150 publications, a clear trajectory emerges: from fundamental design theory through tool development to practical application in warship, submarine and advanced multi-hull projects. Recent outputs (2021-2024) emphasise automation of early-stage synthesis, network-based modelling of complex distributed systems, and integration of operational availability considerations into concept design. Honours & Awards Fellow of the Royal Academy of Engineering (2000) Fellow of the Royal Institution of Naval Architects (RINA) Fellow of the Society of Naval Architects and Marine Engineers (SNAME) William Froude Medal, RINA (2020) – highest award David W Taylor Medal, SNAME (2021) – lifetime contribution Advising & Grant Leadership Since flexible retirement in 2012 he continues to lecture and supervise MSc projects in Naval Architecture, Marine Engineering and Submarine Design CPD courses. He has led or co-led research grants exceeding £2 million from EPSRC, EU and industry (BAE Systems, Rolls-Royce, BMT, Dstl). These projects have funded numerous CASE studentships and collaborative PhD programmes that bridge UCL and industrial stakeholders. Research Team & Industrial Links Professor Andrews heads the Design Research group at UCL, mentoring successive MoD Professors of Naval Architecture and maintaining active Memoranda of Understanding with BAE Systems and other maritime primes. He chairs the tri-annual International Marine Design Conference’s Design Methodology Panel and has delivered keynote addresses worldwide, uniquely representing non-US expertise at successive US Navy Ship Design Process Workshops.

• Naval architecture
• Ship design methodology
• Submarine design
• +5 more

Professor Jess Power serves as Associate Pro-Vice Chancellor for Learning and Teaching Enhancement and Professor of Learning and Teaching at the University of Salford, where she leads the Learning and Teaching Enhancement Centre (LTEC). With over 20 years of teaching experience, she holds prestigious fellowships including Principal Fellow of the Higher Education Academy, Fellow of The Textile Institute, and Fellow of the Chartered Management Institute. Recognized as a National Teaching Fellow in 2016, she has contributed extensively to learning and teaching innovation both within fashion/textiles and across higher education broadly. Professor Power's research spans three interconnected domains: evidence-based pedagogical approaches to enhance employability; technical textile research focusing on clothing size, fit, and 3D garment simulation; and high-performance textile materials assessment. Her work consistently bridges disciplines, connecting fashion/textiles with health, engineering, business, and education to create innovative educational models. Recent publications demonstrate growing emphasis on sustainable fashion, digital transformation in textiles, and inclusive assessment practices that support diverse student populations. Her extensive publication record includes over 100 national and international publications and keynotes, with 15 articles published in 2025 alone covering topics from Ukrainian educational crisis response to sustainable fashion technologies. These works reveal a trajectory toward increasingly interdisciplinary and socially engaged scholarship addressing contemporary challenges in higher education and the fashion industry. National Teaching Fellow (2016) Principal Fellow of the Higher Education Academy Fellow of The Textile Institute Fellow of Chartered Management Institute As an experienced PhD/DBA supervisor and thesis examiner, Professor Power has developed robust frameworks for supporting research students. Her leadership of LTEC has secured both internal and external funding for innovative educational projects, including the internationally recognized 24-hour interdisciplinary challenge and initiatives addressing BTEC student progression. She actively collaborates across sectors, working with industry partners on sustainable fashion initiatives and with international institutions through The Textile Institute's global network. Under Professor Power's leadership, LTEC has become a dynamic hub for educational innovation at University of Salford, developing visual storytelling approaches to transform academic practice, co-created inclusive assessment principles, and solutions for diverse student populations. The center hosts the annual Festival of Learning and Teaching and produces influential publications that disseminate evidence-based teaching practices across the higher education sector.

• Pedagogical Research
• Learning and Teaching Enhancement
• Interdisciplinary Education
• +7 more

Craig Smith is a Law Lecturer at the University of Salford working within the Salford Business School. He specializes in legal education, legal technology, and AI law, with a research focus on integrating Generative AI into legal education to enhance student engagement and develop critical legal skills. As a strong advocate for embedding AI into law curricula, he ensures students gain both theoretical knowledge and practical competencies necessary for future legal practice in an AI-enabled world. His research interests span the use of Generative AI in teaching, learning, and assessment; the development of digital legal skills; and the ethical, pedagogical, and regulatory implications of AI in legal practice and higher education. With 19 research outputs spanning from 2015 to 2025, his work demonstrates a clear trajectory toward increasingly focusing on AI's role in legal education, with 18 of his 19 publications appearing since 2023. Senior Fellowship (SFHEA) from Advance HE (2022) Excellence in Digital Innovation from Whatuni Student Choice Awards (2021) Craig teaches across undergraduate and postgraduate law programs, leading curriculum innovation projects that embed Generative AI into teaching and assessment. He launched the Digital Skills Initiative to enhance students' confidence in using AI tools and has designed active learning initiatives including simulated assessments and collaborative international projects. As External Examiner at the University of Law since 2023, he contributes to quality assurance in legal education while maintaining his research and teaching commitments at Salford.

• Legal Education
• Artificial Intelligence Law
• Legal Technology
• +4 more

Professor William Holderbaum is a faculty member at the School of Science, Engineering & Environment at the University of Salford, with additional affiliation to the Centre for Future Engineering. His academic career demonstrates sustained research productivity with 46 documented research outputs spanning from 2012 to 2025. Professor Holderbaum's research interests encompass several interconnected domains: Control Systems Theory and Applications Hybrid Dynamical Systems (particularly power converters) Robotics (Geometric Control, nonholonomic systems, Reinforcement Learning) Rehabilitation Engineering (Robust Control Design) Energy Management (Electric Vehicles, Smart Grids, Multiple Agent Systems) Autonomous Vehicles (Motion planning, AI) His recent publication activity (11 papers in 2025, 13 in 2024) reveals a strong emphasis on power systems protection challenges, particularly addressing microgrid protection issues arising from distributed generation integration. He has developed innovative approaches for overcurrent relay coordination, microgrid frequency stability, and protection schemes for inverter-dominated grids. His work also extends to robotics applications in textile manufacturing, wearable sensor technology for gesture recognition, and digital twin applications for power system protection. Professor Holderbaum maintains an active research program with significant recent output, demonstrating continued scholarly productivity and relevance in his fields of expertise. His interdisciplinary approach bridges theoretical control systems with practical engineering applications across multiple domains.

• Control Systems
• Hybrid Dynamical Systems
• Robotics
• +6 more

Dr. Anas Lila serves as a Lecturer in the Department of Architecture and the Built Environment within the Faculty of Environment and Technology at the University of the West of England (UWE Bristol), where he integrates computational methodologies with architectural practice to advance sustainable design solutions. His academic credentials include a BSc, MSc, and Ph.D., complemented by professional recognitions such as Fellow of Advance HE (FHEA) and affiliate membership in the Chartered Institute of Architectural Technologists (CIAT). Research focuses on Artificial Intelligence and Machine Learning applications in architecture, with expertise in 3D Printing , Algorithmic Design , and Parametric Design for optimizing building performance. His work addresses critical challenges in energy efficiency, thermal comfort, and emission reduction through computational urban modeling and building physics simulation, particularly in diverse climatic contexts like Egypt. He supervises PhD candidates in computational architecture/urbanism and examines master's theses across four specialized programs, while teaching design studios and technical modules including Urban Sentience (module lead), Computing Complexity, and structural engineering fundamentals. Key research initiatives: Principal Investigator (2021-2022): "A Building-urban Approach For Energy Efficiency, Thermal Comfort And Emission Reduction" funded by Cresmi Challenge Prize (British Council/UCL) Research Associate (2021): "Architects and Engineers approaches to automating early stage environmental performance" with private sector/internal funding Research Assistant (2018-2020): "Computing Craft: Manufacturing cob structures using robotically controlled 3D printing" funded by EPSRC Professional distinctions: Fellow of Advance HE (FHEA) Member of International Building Performance Simulation Association (IBPSA) CIAT affiliate member Member of Egyptian Engineers Syndicate and Egyptian Architects Association (former VP of Youth Committee) Scientific committee member/reviewer for SIMAUD conferences (2018-2021)

• Artificial Intelligence
• Machine Learning
• 3D Printing
• +6 more

Jun Wang is a Professor of Information and Data Science in the Department of Computer Science at University College London. He serves as the Founding Director of the MSc Web Science and Big Data Analytics program and is the Co-founder and Chief Scientist of MediaGamma Ltd (acquired), a UCL startup focused on AI for intelligent audience decision-making. His educational background includes: Doctor of Philosophy from Technische Universiteit Delft (2007) Master of Science from National University of Singapore (2003) Bachelor's degree from Southeast University Nanjing (1997) Professor Wang's primary research focuses on AI and intelligent systems, with particular expertise in multiagent reinforcement learning, deep generative models, and their applications across several domains. His work spans information retrieval, recommender systems and personalization, data mining, smart cities, bot planning, and computational advertising. His research has practical implications in healthcare, robotics, and intelligent systems for decision-making, aligning with Sustainable Development Goal 3 (Good Health and Well-Being). His recent publications demonstrate a strong trend toward integrating large language models with reinforcement learning techniques to create more efficient and capable systems. The research spans healthcare applications, robotics, information systems, and strategic decision-making, with an emphasis on privacy preservation, efficient computation, and multi-agent coordination. Professor Wang has received several prestigious awards: Beyond Search – Semantic Computing and Internet Economics award from Microsoft Research Yahoo! FREP Faculty award UCLB One-to-Watch award 2016 for MediaGamma First place in global real-time bidding algorithm contest (80+ participants worldwide) Multiple Best Paper awards With over 15 years of experience, Professor Wang has advised numerous startups including Last.Fm, Passiv Systems, Massive Analytic, Context Scout, and Polecat. He has also collaborated with major industry players such as BT, Microsoft, Yahoo!, Alibaba, and Didi. His knowledge transfer activities bridge academic research with practical industry applications. Professor Wang has developed the Information Retrieval and Data Mining MSc module and the MSc/MRes programme on Web Science and Big Data Analytics. He also teaches a multiagent AI MSc module, sharing his expertise in cutting-edge AI techniques with the next generation of computer scientists.

• Artificial Intelligence
• Reinforcement Learning
• Multi-agent Systems
• +7 more

Jay Deslauriers serves as a Research Fellow at the University of Westminster's Centre for Parallel Computing and holds a Teaching Fellow position at Imperial College London spanning both the Graduate School and Business School. With five years at Westminster following prior service as a full-time Lecturer in the School of Computer Science & Engineering, his career bridges advanced cloud research and technical education. His research focuses on cloud and container orchestration with emphasis on vendor-agnostic solutions across the cloud-edge continuum. Key projects include leading MiCADO framework development for the EU Horizon 2020 DIGITbrain (Digital Twins in Manufacturing) and ASCLEPIOS (secure healthcare cloud platform) initiatives. His technical expertise spans Kubernetes, Docker, TOSCA standards, and infrastructure-as-code implementation. Research outputs show consistent publication trends in Decentralized orchestration frameworks (2023-2025) Digital twin deployment systems (2021-2022) Cloud-agnostic application management (2018-2020) with recent work emphasizing microservices in edge computing environments. His professional engagement includes Society of Research Software Engineering membership (since 2019) AdvanceHE fellowship (since 2020) supporting his dual focus on technical infrastructure and research education. Current supervision interests center on cloud/container orchestration, Docker/Kubernetes implementation, and statistical methods for resource optimization. His MiCADO framework remains central to multiple EU-funded projects with ongoing development for cloud-edge continuum applications.

• Cloud Orchestration
• Containerization
• Digital Twins
• +6 more

Dr. Qunfen Qi is a Senior Lecturer at the University of Bristol's School of Electrical, Electronic and Mechanical Engineering, where she leads groundbreaking research at the intersection of mathematics, informatics, and manufacturing. With over 13 years of experience, she specializes in developing smart decision-making tools for product design and inspection using category theory as a foundational mathematical language. Her work bridges multiple disciplines to create more intelligent and transparent manufacturing systems that can 'think' like human experts. Dr. Qi's research focuses on knowledge modeling for manufacturing, with particular emphasis on smart information systems, abstract mathematical theory (category theory), Geometrical Product Specifications and Verification (GPS), Additive Manufacturing, surface design, and metrology. Her unique approach applies category theory to simplify complex relationships in manufacturing data, enabling better decision-making in digital manufacturing environments. This work has become increasingly relevant as manufacturing embraces advanced digital technologies like cyber-physical systems, IoT, and AI, where managing multiple levels of abstraction is critical. Her publication record shows a clear trajectory toward more sophisticated applications of mathematical frameworks in manufacturing, with growing integration of category theory with AI approaches, particularly in explainable AI for manufacturing contexts. Recent work demonstrates increasing practical applications in additive manufacturing, quality control, and digital twin development, with strong emphasis on how these systems can explain their decisions at multiple levels of detail. Scientific Awards and Recognition UKRI EPSRC Innovation Fellow (2018-2022) EPSRC Peer Review College Member (ranked top 4% for participation in 2020/21) Project lead for ISO/TR 24331-2 Geometrical Product Specification development ISO Technical Committee Expert (TC 213, TC 184 WG26, JWG 21) BSI Technical Committee Member (AMT_4, TPR1/1, TPR1/8, TPR1/9) Co-Chair of CIRP CAT 2024 (18th International Conference on Computer-Aided Tolerancing) Dr. Qi actively recruits PhD students interested in explainable machine learning, mathematical AI foundations, and smart manufacturing applications. Her research portfolio includes four major projects totaling significant funding, including an EPSRC Innovation Fellowship for 'A semantic infrastructure for advanced manufacturing' and a Royal Society International Exchanges project on mathematical foundations for digital manufacturing systems. She maintains strong international collaborations, particularly with Italian institutions like Politecnico di Milano and CNR-STIIMA, reflecting her global impact in advancing the mathematical foundations needed for next-generation intelligent manufacturing systems.

• Knowledge modelling for manufacturing
• Smart information systems
• Category theory
• +7 more

Dr. Stylianos Sapountzis serves as Programme Leader for the MSc in Project Management at Salford Business School, University of Salford, where he leads modules including Project Management Leadership and Skills (PG), Advanced Project and Logistic Management (PG), and Project Management (UG). With an industrial background in manufacturing management within the electronics sector, he brings practical expertise to his academic role, having previously worked as a production manager and process engineer focusing on production optimization and new product introduction. His educational background includes: PG Cert Academic Practice (2015, University of Salford) PhD in Project Management (2013, University of Salford) PgDip Advanced Manufacturing Systems (1998, University of Salford) BSc (Hons) Manufacturing with Languages (1997, Manchester Metropolitan University) Dr. Sapountzis specializes in benefits realization frameworks, particularly his BeReal process for healthcare infrastructure projects, with research spanning value generation in projects, lean manufacturing applications, and digital transformation in project management. His scholarly work demonstrates a clear trajectory from healthcare infrastructure research toward contemporary applications of AI in project management and supply chain optimization, with recent publications examining digital transformation challenges in UK higher education and AI applications in negotiation activities. His research portfolio shows strong interdisciplinary connections between traditional project management principles and emerging digital technologies, with significant contributions to understanding how lean thinking can be applied across diverse sectors including healthcare, construction, and pharmaceutical manufacturing. The publication record reveals consistent output with increasing focus on digital transformation and AI applications since 2020. As a key member of the Health and Care Infrastructure Research and Innovation Centre (HaCIRIC), Dr. Sapountzis has presented research to international audiences and national bodies including the Department of Health, NHS Trusts, and Manchester City Council. His teaching expertise encompasses project planning and delivery tools, stakeholder management, and the Lean Toolbox, bridging theoretical concepts with practical industry applications developed through his earlier manufacturing career.

• Benefits Realisation in Project Management
• Value Generation in Projects
• Lean Manufacturing and Process Optimisation
• +3 more

Sarab Sethi is a Lecturer in the Department of Life Sciences at Imperial College London, where he develops computational approaches for biodiversity monitoring through ecoacoustics. His work integrates machine learning, sensor technology, and ecological fieldwork to address conservation challenges, particularly in tropical ecosystems. His research focuses on advancing soundscape ecology through innovative methodologies including random forest analysis of avian migration patterns, development of low-power acoustic monitoring systems, and standardization of acoustic indices. Key contributions involve demonstrating how soundscapes predict species occurrence in tropical forests and creating open-source tools like the SAFE Acoustics network for real-time ecosystem monitoring. Recent publications reveal a strong trend toward scalable biodiversity assessment solutions, with increasing emphasis on robotics-assisted surveys, virtual acoustics validation, and robust machine learning models that function effectively under noisy field conditions. His work consistently bridges theoretical ecology with practical conservation applications. Dr. Sethi actively contributes to scientific discourse through peer review for high-impact journals including Nature , Nature Reviews Biodiversity , and Proceedings of the National Academy of Sciences , demonstrating significant scholarly engagement within the ecological research community. He leads the development of critical infrastructure for ecoacoustic research, including the Acoustic Index User's Guide and validation frameworks for ecoacoustic metrics, which enable standardized biodiversity assessment across global ecosystems. His fieldwork in Malaysian Borneo provides foundational data for tropical conservation applications.

• Ecoacoustics
• Biodiversity Monitoring
• Machine Learning Applications
• +5 more

Dr. Lee Christie is a Research Fellow at Robert Gordon University's School of Computing, Engineering & Technology, where he conducts research in optimization and artificial intelligence. He is affiliated with the Complex Optimisation Research Group and maintains connections with the National Subsea Centre through his research on net-zero operations. His educational background includes: BSc (Hons) in Computer Science from Robert Gordon University (2003-2007) MSc in Information Engineering (Distinction) from Robert Gordon University (2009-2011, part-time) PhD in Computational Intelligence from Robert Gordon University (2011-2016) Dr. Christie's research primarily focuses on combinatorial optimization, structure learning, and blockchain technologies. He investigates how to make non-deterministic solvers more transparent through trajectory mining and feature extraction. His work bridges theoretical optimization techniques with practical applications in transportation systems (particularly connected autonomous vehicles), renewable energy (wind farm optimization), and supply chain management. He has published extensively on explainable metaheuristics, with a growing emphasis on making optimization algorithms interpretable for end-users while maintaining effectiveness. His recent publications (2021-2025) demonstrate a clear research trajectory toward explainable AI for optimization algorithms, with applications spanning transportation systems, renewable energy infrastructure, and complex supply chains. These works showcase his ability to translate theoretical advances into practical solutions for real-world problems with societal impact. Dr. Christie has secured research funding for projects including the A.R.T. Forum NSR (2019-2022), which developed implementation roadmaps for automated road transport in the North Sea Region. He teaches programming for business analytics courses and actively contributes to the Aberdeen Python User Group as a steering committee member. His academic service includes supervision of PhD students, with Dr. Martin Fyvie recently completing a dissertation on 'Explainability of Non-Deterministic Solvers' under his guidance as second supervisor. Dr. Christie maintains active collaborations with researchers including John McCall, A.-C. Zăvoianu, and A.E.I. Brownlee, resulting in consistent publication output across reputable venues in evolutionary computation and artificial intelligence.

• Combinatorial Optimisation
• Explainable AI
• Metaheuristics
• +7 more