Dr Henry Moss is a Researcher at the Department of Applied Mathematics and Theoretical Physics within the School of Physical Sciences at the University of Cambridge. His work focuses on machine learning applications in climate modeling, Bayesian optimization, and Gaussian processes, bridging computational mathematics with environmental science and chemistry. His research interests include: Bayesian optimization for environmental and chemical systems Reinforcement learning in climate modeling Gaussian processes for molecular property prediction High-throughput machine learning in scientific domains Interpretable AI for coastal flooding prediction Hybrid ML-physics modeling Dr Moss's publications highlight his contributions to federated learning for climate models, sparse Gaussian process techniques, and multi-objective optimization frameworks. These works span applications in weather prediction, chemical engineering, and oceanography. Email: hwm26@cam.ac.uk
Dr Andrew Rhead is a Senior Lecturer in the Department of Mechanical Engineering at the University of Bath, specializing in aerospace composites and damage tolerance analysis. His research focuses on impact damage detection, failure mechanism modeling, and Non-Destructive Evaluation (NDE) techniques for composite structures. MSci in Mathematical Sciences (Dynamical Systems) - University of Bristol (2006) PhD in Composite Damage Tolerance - University of Bath (2009) His work develops computationally efficient analytical models for compression after impact (CAI) strength prediction in composite laminates, surpassing traditional finite element methods. Key projects include hydrogen storage systems for aircraft, cryogenic composite testing, and steered fiber manufacturing optimization. Active in 10 projects including ASPIRE and HyFIVE Collaborates with Airbus, GKN Aerospace, and EPSRC Research trends show emphasis on sustainable aviation materials, structural battery integration, and advanced testing methodologies. Current affiliations include the Institute for Mathematical Innovation (IMI) and Centre for Integrated Materials, Processes & Structures (IMPS).
Dr. Mo Adda is a Principal Lecturer at the University of Portsmouth's School of Computing, part of the Faculty of Technology. He holds a PhD in Distributed Systems and Parallel Processing from the University of Surrey. His research focuses on network security, distributed systems, wireless networks, and cybercrime prevention. He leads projects in the Centre for Cybercrime and Economic Crime, exploring fault management in networks, blockchain applications, and IoT forensics. With 16 supervised theses, he advises on topics like energy-efficient cloud systems and machine learning for environmental modeling. His work bridges academia and industry, addressing challenges in software-defined networks, traffic control, and secure data sharing in social networks. Education: PhD in Distributed Systems (University of Surrey) Affiliations: Centre of Excellence in Defence, Risk & Resilience; Portsmouth Centre for Advanced Materials and Manufacturing Research Interests Dr. Adda's research spans: Network security and fault detection mechanisms Blockchain applications in IoT and forensics Energy-efficient cloud data center optimization Machine learning for climate modeling Self-organizing network protocols Grants & Collaborations His projects include collaborations with industry partners on secure data leakage detection in cloud systems and resilient wireless protocols for harsh environments. He has pioneered fault classification systems using clustering algorithms and fuzzy logic. Labs & Teams He contributes to the Centre for Cybercrime and Economic Crime, focusing on digital forensics and network intrusion analysis. His team develops frameworks for privacy management in social networks and proactive routing in software-defined networks.
Professor Omar Matar is a Professor of Fluid Mechanics and RAEng/PETRONAS Research Chair in Multiphase Fluid Dynamics at the Department of Chemical Engineering, Imperial College London. He leads the Matar Fluids Group, focusing on interfacial fluid mechanics, multiphase flows, computational fluid dynamics (CFD), and applications in energy, manufacturing, and nanotechnology. His roles include Head of Department of Chemical Engineering, Director of the PETRONAS Centre for Engineering of Multiphase Systems (PETCEMS), and Editor-in-Chief of the Journal of Engineering Mathematics. Education: PhD in Chemical Engineering, Princeton University (1993) MEng Chemical Engineering, Imperial College London (1989) Research Interests: Interfacial fluid mechanics, multiphase flows, CFD, and machine learning 2D materials exfoliation and scale-up, immersive technologies (AR/VR) Applications in energy systems, nanotechnology, and personalized education Awards: Fellow of the Royal Academy of Engineering (2020) Recipient of the Imperial College President’s Medal (2020) EPSRC Programme Grant Principal Investigator (MEMPHIS, PREMIERE) Grants & Projects: MEMPHIS: £5M EPSRC-funded Programme Grant (2012–2017) PREMIERE: EPSRC Programme Grant (2019–present) PETCEMS: PETRONAS-funded Centre for Multiphase Systems Engineering Labs & Collaborations: Leads the Matar Fluids Group, collaborating with institutions like UCL, University of Edinburgh, and industry partners such as BP and First Light Fusion. Active in developing high-performance CFD codes (e.g., BLUE) and machine learning-driven models for multiphase systems.
Shafiul Monir serves as Senior Lecturer in Engineering, Associate Dean (International and Partnerships), and Programme Leader for the MSc in Engineering at Wrexham University, with contact details including Room D30, phone 01978 293151, and email s.monir@wrexham.ac.uk. His academic qualifications include: BEng (Hons) in Aeronautical Mechanical Engineering from Wrexham University (2008) MSc in Aeronautical Engineering specializing in Computational Fluid Dynamics (CFD) modelling PhD in Low Carbon Research from University of Wales (awarded 2018) under Wrexham University's auspices Monir's research centers on solar photovoltaic technology development, particularly applying computational fluid dynamics to optimize thin-film deposition processes for Cadmium Telluride (CdTe) solar cells. His expertise spans atmospheric pressure metalorganic chemical vapour deposition (AP-MOCVD), thin-film uniformity challenges, and renewable energy systems engineering, with significant contributions to advancing sustainable photovoltaic manufacturing techniques. He is a core member of the Centre for Solar Energy Research (CSER), participating in the Solar Photovoltaic Academic Research Consortium (SPARC) Cymru project funded by the Lower Carbon Research Institute (LCRI). His doctoral research received support through the Knowledge Economy Skills Scholarships (KESS) program, European Social Fund (ESF), and Scanwel Ltd sponsorship.
Professor Thomas Blumensath is a Professor of Signal and Image Processing at the University of Southampton and a Fellow at the Alan Turing Institute. He is the Academic Lead in Image Processing and Reconstruction at the University's μ-VIS X-ray Imaging Centre and Director of Research at the Institute of Sound and Vibration Research (ISVR). His research focuses on advanced algorithms for solving inverse problems in tomographic imaging, combining machine learning, optimization, and statistical methods. Key areas include X-ray tomography strategies, GPU-accelerated reconstruction, and multimodal imaging applications. Education: B.Sc. (Hons) Music Technology and Audio System Design, University of Derby (2002) PhD in Electronic Engineering (Bayesian Signal Processing), University of London (2006) Research Interests: Professor Blumensath's work spans theoretical and applied signal/image processing, with emphasis on tomographic imaging techniques. His current projects address efficient reconstruction methods, spectral X-ray CT, and applications in manufacturing and plant science. He collaborates with advanced imaging facilities like Diamond Light Source and ISIS neutron imaging beamline. Key Contributions: His research bridges computational methods (e.g., compressed sensing) with practical imaging challenges, including limited-angle tomography and stereo imaging strategies. He leads the National Research Facility for Lab X-ray CT and has developed the TIGRE reconstruction toolbox. Grants & Projects: Active funding includes EPSRC projects on tomographic sensitivity monitoring and CT-based manufacturing inspections. Completed projects cover constrained reconstruction, AM process verification, and industrial CT metrology. Awards: Alan Turing Institute Fellowship Teaching & Leadership: He teaches modules on machine learning, biomedical image processing, and robotics. Leads the BEng Control Engineering program at the Joint Education Institute with Harbin Engineering University. Labs/Teams: Active in the Signal Processing, Audio and Hearing research group (SPAH) and the Institute for Life Sciences. Oversees the μ-VIS X-ray Imaging Centre's research initiatives.
Professor Shaomin Wu is a faculty member at the University of Kent's Kent Business School, where he holds the academic rank of Professor of Business/Applied Statistics. He earned an MSc and PhD in applied statistics and has extensive industry experience, including a five-and-a-half-year stint at a global manufacturer in Shanghai before moving to the UK in 2001. He has held roles as a postdoctoral researcher and lecturer before joining Cranfield University and later the University of Kent. His research focuses on recurrent event data analysis, machine learning, and reliability mathematics, with funding from the EPSRC and ESRC. His research projects include managing risk in warranty servicing policies, smart data analytics for local government, and sustainable supply chain demand forecasting. He teaches modules such as risk analysis, reliability engineering, and machine learning. Currently supervising PhD students in time series forecasting, explainable AI, and recurrent event data analysis, he also serves as a co-chair of international conferences, editorial board member, and external examiner for doctoral degrees. Notably, he ranks among the top 2% of global scientists by Stanford University. His work integrates machine learning with business analytics, resilience engineering, and environmental sustainability. Key contributions include IoT-driven resilience methodologies for smart grids and unmanned systems, as well as frameworks for corporate carbon disclosure and maintenance optimization under uncertainty.
Dr. Artin Backtash-Rad is a Senior Lecturer in Global Strategy & International Business at the Surrey Business School, University of Surrey, where he also serves as the Director of the MSc International Business Management programme. He holds a PhD in Global Strategic Management from Royal Holloway, University of London, an MBA in International Management from Carleton University, Canada, and a BSc in Industrial Management from the University of Tehran, Iran. He has held academic positions at University College London, Royal Holloway, Cardiff Metropolitan University, and the University of South Wales. BSc in Industrial Management, University of Tehran, Iran MBA in International Management, Carleton University, Canada PhD in Global Strategic Management, Royal Holloway, University of London Artin's research focuses on Global Strategic Management, with a particular emphasis on strategy implementation. His doctoral research involved a large-scale comparative study across 20 sectors in 20 countries, resulting in a comprehensive model for corporate-level strategy execution. His work integrates resource-based, industry, and institutional perspectives to develop a holistic theory of strategy implementation. He has conducted extensive research on barriers to implementation, supply chain strategies, manufacturing strategies, and transcontinental investments. His recent publications reflect a strong trend in developing taxonomies and theoretical models in strategic management, particularly in international and cross-sectoral contexts. He frequently presents at top-tier conferences such as the Academy of International Business (AIB), British Academy of Management (BAM), and Euro-Asia Management Studies Association (EAMSA), with recent work focusing on organizational culture transfer, research populations, and Europeanization of strategy. Artin is actively involved in academic service and leadership: Director of MSc International Business Management Member of the Doctoral Programmes Review Committee Personal Tutor for 22 students Work Placement Programme Tutor He supervises postgraduate research, currently guiding two PhD students, and has previously supervised numerous master’s and MBA dissertations across multiple institutions. His teaching spans strategic management, international business, entrepreneurship, research methodology, and operations management at undergraduate and postgraduate levels. Artin is affiliated with leading academic organizations: Academy of International Business British Academy of Management Euro-Asia Management Studies Association
Katrina Morgan-Innes is a Lecturer (Assistant Professor) at the School of Electronics and Computer Science, University of Southampton. Her research focuses on advanced flexible materials for energy harvesting and storage, leveraging semiconductor industry fabrication techniques to develop wearable thermoelectric devices and next-generation batteries. She leads the Morgan Materials and Devices for Energy (MADE) research group and a £220k EPSRC New Horizons grant (Smart Cloth). Her work emphasizes commercial scalability and integration of 2D materials with flexible substrates. Education: MPhys in Physics (University of Sussex, 2011), CASE Award PhD in Electronics and Computer Science (University of Southampton, 2016–2022). Previous roles include Photonics Development Engineer at the AIM Photonics Programme (SUNY) and Visiting Fellow at the Optoelectronics Research Centre. Research interests include energy harvesters, flexible wearables, 2D materials, and nanofabrication. She has pioneered scalable manufacturing methods for photonic and energy devices and contributed to chalcogenide material applications. Her research group aims to create fully flexible systems enabling integrated sensing, power, and communication on lightweight platforms. Key grants include EPSRC funding for wearable thermoelectric generators and collaborations like the ChAMP/WAFT-funded projects on flexible ion sensors and 3D nanophotonics. She has published in high-impact journals (e.g., ACS Applied Materials and Interfaces , npj 2D Materials and Applications ) and conferences, focusing on thermoelectric materials, photonic heterostructures, and scalable manufacturing. Awards: UNSW Women in Engineering Visiting Fund (2019), Top 100 Physics Paper (2020), Outreach Engagement Award (2016) Labs/Teams: Morgan MADE Group, Collaboration with Optoelectronics Research Centre and Zepler Institute Advocacy: Chair of WiSET+ (University-wide STEM+ Equality Committee), founder of Early Career Researcher Forum
Miguel Rodrigues is a Professor of Information Theory and Processing at University College London's Department of Electronic & Electrical Engineering. He leads the Information, Inference and Machine Learning Lab at UCL and serves as the founder and director of the master programme in Integrated Machine Learning Systems. Rodrigues is also the UCL Turing University Lead and a Turing Fellow with the Alan Turing Institute, the UK National Institute of Data Science and Artificial Intelligence. His academic background includes an undergraduate degree in Electrical and Computer Engineering from the Faculty of Engineering of the University of Porto, Portugal, and a PhD in Electronic and Electrical Engineering from University College London. He has held appointments at prestigious institutions worldwide including Cambridge University, Princeton University, Duke University, and the University of Porto. Dr. Rodrigues's research spans information theory, information processing, and machine learning. His work has attracted over £5 million in funding from competitive national and international funding bodies and resulted in more than 250 publications with over 8000 citations in leading journals and conferences, including top AI venues like NeurIPS, ICML, and ICLR. His recent publications demonstrate a strong focus on multimodal learning, machine learning security, climate modeling with satellite data, and applications of AI in healthcare and precision medicine. His work shows increasing interdisciplinary collaboration across fields from climate science to pharmaceutical engineering. IEEE Communications and Information Theory Societies Joint Paper Award 2011 Fellow of the Institute of Electronics and Electrical Engineers (IEEE) Prize for Merit from the University of Porto Prize Engenheiro Cristian Spratley Prize Engenheiro Antonio de Almeida Fellowships from the Portuguese Foundation for Science and Technology Fellowships from the Foundation Calouste Gulbenkian Dr. Rodrigues has served as Editor for IEEE BITS – The Information Theory Magazine and IEEE Transactions on Information Theory, among other editorial roles. He consults widely in machine learning and AI with government institutions, funding agencies, industry, and startups, and sits on committees responsible for AI standardization such as the BSI Art/1 working group. His leadership extends to directing research labs and educational programs focused on advancing machine learning systems. He leads the Information, Inference and Machine Learning Lab at UCL, which focuses on fundamental aspects of information theory and their applications to machine learning and data processing. The lab works on both theoretical foundations and practical implementations of learning systems.
Professor Terry Rudolph is a Professor of Quantum Physics at the Department of Physics within the Faculty of Natural Sciences at Imperial College London. His affiliations include the Quantum Engineering, Science and Technology group, Quantum Optics and Laser Science Group, and The Light Community. His research focuses on quantum-anything, encompassing optical physics, quantum computing, photonics, and related interdisciplinary fields such as nanotechnology and communications technologies. Rudolph’s work emphasizes photonic quantum computing architectures, entanglement generation, and fault-tolerant quantum systems. His recent publications highlight advancements in cluster state generation, photonic multiplexing, and reconfigurable entangling systems. He has contributed to scalable quantum hardware design, including silicon photonic platforms and error-correction protocols. His academic contributions span theoretical and experimental quantum mechanics, with a focus on bridging quantum theory and practical implementation. Notable themes in his research include deterministic teleportation, photonic integrated circuits, and fusion-based quantum computing. He has also engaged in educational initiatives to introduce quantum information science to high-school students. Affiliations: Quantum Optics and Laser Science Group, Quantum Engineering Centre, and The Light Community at Imperial College London.
Professor Daniel Eyers is a Professor of Manufacturing Systems Management at Cardiff Business School, Cardiff University , where he also serves as Director of Quality Assurance & Enhancement. He is co-director of the Centre for Advanced Manufacturing Systems (CAMSAC) and Cardiff University RemakerSpace , highlighting his leadership in sustainable and advanced manufacturing innovation. Professor of Manufacturing Systems Management, Cardiff University (2024–present) Co-Director, Centre for Advanced Manufacturing Systems (CAMSAC) (2024–present) Co-Director, Cardiff University RemakerSpace (2020–present) External Advisor, Open University (2022–present) His research focuses on the strategic management of advanced manufacturing technologies , particularly Additive Manufacturing (3D printing) , within operations and supply chain contexts. He explores how digital technologies enhance supply chain flexibility, sustainability, and performance. His work spans flexible manufacturing systems, servitization, and change management in industrial settings. His recent publications (2020–2025) reveal a strong trajectory in AI-human collaboration in decision-making , sustainable manufacturing , urban logistics , and the integration of 3D printing in circular economies. Themes include risk management, digital transformation, and the strategic impact of emerging technologies on operations. He frequently publishes in top-tier journals such as International Journal of Operations and Production Management , Production Planning and Control , and Omega . CEng, Engineering Council (UK) FHEA, Higher Education Academy ESRC Early Career Impact Acceleration Fellowship Daniel Eyers actively supervises PhD, MSc, and MBA students and has attracted over £2.5 million in research funding from research councils, the Welsh Government, and industry. He contributes to academic program design and quality assurance, serving on university committees and as an external examiner for other institutions. He is deeply engaged in applied research with industrial partners, reflecting his background in commercial manufacturing. His leadership in research centers and commitment to sustainability, digital innovation, and education underscore his role as a key figure in modern operations management scholarship.
Tingliang Huang holds concurrent roles as the Amazon Distinguished Professor of Business Analytics at the University of Tennessee's Haslam College of Business and Honorary Professor at the UCL School of Management. He earned his PhD from Northwestern University's Kellogg School of Management. His research focuses on business analytics, AI-driven strategies, supply chain optimization, and behavioral operations, with notable contributions to Marketing Science, Management Science, and Production and Operations Management. Affiliations: Amazon Distinguished Professor, Haslam College of Business, University of Tennessee Honorary Professor, UCL School of Management Former tenured Associate Professor at Boston College's Carroll School of Management Education: PhD in Management, Kellogg School of Management, Northwestern University (2011) M.S. and B.S. from University of Science and Technology of China (USTC) Research Interests: Huang’s work bridges analytics and operations, exploring topics like opaque selling, bounded rationality in consumer decisions, supply chain dynamics, and sustainable operations. He has pioneered frameworks for probabilistic selling and dynamic pricing under uncertainty. His interdisciplinary approach integrates behavioral economics and big data analytics. Publications: Over 20 peer-reviewed articles in top journals, emphasizing service systems, supply chain strategy, and marketing-operations interfaces. Recent work explores AI's societal impacts and algorithmic targeting in vertical markets. Awards: 2025 Vallett Family Outstanding Researcher Award 2018 POMS Wickham Skinner Early Career Award 2015 POMS Best Paper Award Multiple Meritorious Service Awards (M&SOM, Management Science) Editorial Roles: Senior Editor at Production and Operations Management, Associate Editor at Manufacturing & Service Operations Management, Decision Sciences, and others. He also serves on editorial review boards for leading journals. Teaching & Mentorship: Award-winning educator recognized as Carroll School Teaching Star (2021). Advises doctoral students at UCL, UTK, and Chinese institutions, with placements at top schools like George Mason University and USTC. Labs & Teams: Leads the Business Analytics PhD Program at UTK and collaborates on AI ethics research through cross-institutional projects.
Dimitrios Tsaoulidis is a Senior Lecturer in Chemical Engineering at the University of Surrey and an Honorary Lecturer at University College London . He holds a PhD in Chemical/Nuclear Engineering and a Diploma in Chemical Engineering. University roles: Academic Integrity Officer, Senior Personal Tutor, Disability & Neurodiversity Representative Research spans clean energy (nuclear, bio, solar), healthcare (bioprocess scalability), and manufacturing using process intensification and microfluidics . His work combines experimental investigation , CFD simulations , and scale-up optimization for multiphase reactors . Notable research trends include: 15+ publications (2012–2023) on uranium extraction , biodiesel production , and pharmaceutical microfluidics , with grants from UKRI and Innovate UK . Scientific Awards : David Newton’s Award for Sustainability (UCL) Springer Thesis Award Fellow of the Higher Education Academy (FHEA) Associate Member of the Institution of Chemical Engineers (AMIChemE) Research Collaborations : Academic : Prof Panagiota Angeli (UCL), Prof Eric Fraga (UCL), Dr Maryam Parhizkar (UCL) Industrial : UK Atomic Energy Authority, National Nuclear Laboratory, GSK, Greenergy Ltd, Armfield Dr Tsaoulidis supervises PhD students (e.g., Mustapha Hamdan, Anna Tsitouridou) and PDRA staff (e.g., Dr Jamshid Zarkesh) in projects related to solar energy systems , nuclear fuel cycles , and pharmaceutical automation .
Professor Howard Stone is a faculty member at the University of Cambridge, affiliated with the Department of Materials Science and Metallurgy. He has progressed through academic ranks, including Professor of Metallurgy (2021), Reader in Metallurgy (2017), and Lecturer in Metallurgy (2012). PhD (University of Cambridge, 2000) MA (University of Cambridge, 1995) His research focuses on metallurgy and materials science , particularly Nickel-Based Superalloys , High-Entropy Alloys , and Titanium Alloys . Key areas include microstructural evolution under thermal stress, oxidation resistance, and additive manufacturing techniques like laser powder bed fusion. Professor Stone’s recent publications highlight trends in superalloy design , phase stability , and additive manufacturing . Topics include gamma prime precipitation, lattice misfit analysis, and oxidation behavior modification. He is associated with the Rolls-Royce UTC (University Technology Centre) at Cambridge, which focuses on advanced metallurgical research and industrial collaboration.
