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Dr Cinzia Giannetti

Dr Cinzia Giannetti

Associate Professor, Engineering

Telephone number

+44 (0) 1792 602323

Email address

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Research Links

Available For Postgraduate Supervision

About

Dr Giannetti is a researcher in Smart Manufacturing technologies and an EPSRC UKRI Innovation Fellow (2018-2021). Her research is driven by a passion for developing innovative technologies and tools that can have a transformational impact on our lives, society and the economy.

Cinzia's mission is to support the growth of the UK Manufacturing sector through development of autonomous, collaborative and intelligent production systems by using knowledge-intensive advanced digital technologies. Cinzia is co-Investigator and part of the multidisciplinary leadership team in the EPSRC Centre for Doctoral Training in Enhancing Human Interactions and Collaborations with Data and Intelligence Driven Systems, which train and nurture future leaders in digital data-driven innovations.

In addition to academic expertise, Dr Giannetti has a strong background in Software Engineering acquired both in commercial and academic environments, with experience in design and development of new products and prototypes in collaboration with a wide range of stakeholders in Universities, SMEs and large organisations.

Areas Of Expertise

  • Manufacturing Systems Engineering
  • Big Data
  • Manufacturing Informatics and IoTs
  • Machine Learning/Deep Learning
  • Artificial Intelligence
  • Process Optimisation

Career Highlights

Teaching Interests

Fellow of Higher Education Academy

Development and teaching of Smart Manufacturing

Research

Dr Cinzia Giannetti is currently EPSRC UKRI Innovation Fellow in Digital Manufacturing.  The main focus of her research fellowship (“Transfer Learning for Robust, Resilient and Transferable Cyber Manufacturing Systems”) is to improve techniques that can be used to develop digitalised manufacturing systems to reduce existing inefficiencies in production processes that impact on production costs, unplanned downtime, quality and yields. Using real world datasets provided by industrial partners (Tata Steel, Crown Technology and Vortex IoT) Cinzia aims to develop and deploy data driven computational models that will enable to monitor and predict process conditions and advise on best actions to increase operational efficiency of production processes.

An important outcome of Dr Giannetti's research is to improve our understanding of the benefits of adoption of Industrial Digital Technologies, and their value, and inspire confidence for manufacturers and suppliers to invest in this area, contributing to the UK to become a leader in digital manufacturing. 

Collaborations

Dr Cinzia Giannetti is co-Investigator and part of the multidisciplinary leadership team in the EPSRC Centre for Doctoral Training in Enhancing Human Interactions and Collaborations with Data and Intelligence Driven Syste