Professor Cinzia Giannetti is a Fellow of the Learned Society of Wales and Professor of Digital Manufacturing in the Wolfson School of Mechanical, Electrical and Manufacturing Engineering at Loughborough University. She joined Loughborough in 2026 following an academic career at Swansea University, where she held the positions of Senior Lecturer, Associate Professor and Professor of Mechanical Engineering. During her time at Swansea, she also served as Funding Co-Director of the Materials and Manufacturing Research Institute (M2RI), providing strategic leadership for one of the University's largest interdisciplinary research communities.
Before entering academia, Cinzia spent over a decade in industry working in software engineering, telecommunications and product innovation. She held technical and engineering management roles at Siemens, Motorola and NextGen Holdings, leading the development of large-scale software systems and multidisciplinary engineering teams. This industrial experience continues to shape her research, providing a strong focus on delivering practical, impactful digital technologies for manufacturing.
Cinzia obtained a Degree in Applied Mathematics from the University of Pisa, before moving to the UK. She later completed an Engineering Doctorate (EngD) in Advanced Manufacturing and a Postgraduate Certificate in Higher Education (PGCertHE) at Swansea University.
Her research career has focused on advancing Industrial Artificial Intelligence, Digital Twins and data-driven manufacturing technologies that improve the sustainability, productivity and resilience of manufacturing systems. She has led and contributed to major UKRI-funded research programmes, working closely with industrial partners across the steel, automotive, advanced materials and manufacturing sectors to translate cutting-edge research into industrial practice.
Qualifications
- PGCertHE (Postgraduate Certificate in Higher Education), Swansea University, UK (2018)
- Engineering Doctorate (EngD) in Advanced Manufacturing, Swansea University, UK (2015)
- PGCE in Mathematics Education, Swansea Metropolitan University, UK (2009)
- MSc in Applied Mathematics, University of Pisa, Italy (1996)
Professor Cinzia Giannetti's research focuses on developing the next generation of human-centric digital manufacturing technologies that enable more sustainable, resilient and intelligent manufacturing systems.
At Loughborough University, Professor Giannetti leads a research theme focused on Trustworthy Industrial AI for Sustainable Manufacturing, advancing the next-generation Digital Twins that combine artificial intelligence, engineering knowledge and human expertise to accelerate the transition to Industry 5.0.
Her research addresses the integration of data-driven and physics-based models to create trustworthy Digital Twins capable of monitoring, predicting and optimising manufacturing processes in real time. She has pioneered the application of AI to complex industrial environments, developing solutions for predictive quality, computer vision, predictive maintenance, process optimisation and autonomous decision support.
A central theme of her research is the development of transparent and explainable AI that combines machine learning with engineering knowledge, enabling industrial systems that are not only accurate but also interpretable, robust and deployable in safety-critical manufacturing environments.
Working closely with industrial partners, her research has been successfully applied across the steel, automotive, advanced materials and manufacturing sectors, delivering measurable improvements in product quality, operational efficiency and sustainability.
Research interests
- Human-centric Digital Twins
- Industrial Artificial Intelligence
- Digital Manufacturing
- Hybrid AI and Explainable AI
- Cyber-Physical Systems
- Machine Learning for Manufacturing
- Manufacturing Data Science
- Computer Vision for Industrial Applications
- Predictive Maintenance and Prognostics
- Process Optimisation and Quality Prediction
- Sustainable and Circular Manufacturing
- Industry 5.0
Research Centres and Networks
Honours and Awards
- Elected Fellow of the Learned Society of Wales (LSW) (2026)
- Top 100 Women in Engineering, Women's Engineering Society (WES) (2022)
- UKRI EPSRC Innovation Fellowship (2018–2021)
- Best Paper Award, INISTA Conference (2019) – A Deep Learning Framework for Univariate Time Series Prediction Using Convolutional LSTM Stacked Autoencoders
- Best Student Paper Award, Sustainable Design and Manufacturing Conference (SDM) and UK ICME Exchange Paper and Travel Grant (2014)
Grants and Contracts
- 2025–2032 – IGNITE Sustainable Manufacturing Hub (UKRI EPSRC, £11M) – Co-Investigator and Research Challenge Lead.
- 2019–2026 – SUSTAIN Future Manufacturing Hub (UKRI EPSRC, £10M) – Co-Investigator and Deputy Director (2025–2026).
- 2021–2025 – Materials Made Smarter Research Centre (UKRI EPSRC, £4M) – Co-Investigator, Swansea Principal Investigator and Co-Director.
- 2019–2026 – EPSRC Centre for Doctoral Training in Enhancing Human Interactions and Collaborations with Data and Intelligence Driven Systems (EPIC) (UKRI EPSRC, £5.33M) – Co-Investigator; Lead for Smart Manufacturing and Equality, Diversity and
Inclusion. - 2018–2021 – Transfer Learning for Robust, Resilient and Transferable Cyber Manufacturing Systems (UKRI EPSRC Innovation Fellowship, £586k) – Principal Investigator. · 2020–2021 – Capital Award for Core Equipment (UKRI EPSRC, £125k) – Co-Investigator.
- 2020 – AccelerateAI Equipment Grant (Ser Cymru, £612k) – Co-Investigator. · 2019–2020 – PARSER: Novel LiDAR Sensor for Smart Cities (Innovate UK, £319k) – Principal Investigator. · 2018 – CASMOS: Modular Roofing Innovation (Innovate UK, £71k) – Principal Investigator.