Cristian Genes – University of Sheffield

Cristian Genes 

I received a B.Eng. degree from Gheorghe Asachi Technical University of Iasi, Romania in 2014 and a PhD in Automatic Control and Systems Engineering at The University of Sheffield in 2019. I am currently a Research Associate in the Department of Automatic Control and Systems Engineering at The University of Sheffield, UK. My main research interests include matrix completion, network theory and digital twins.

My research addresses the problem of missing data in high-dimensional datasets. The quantity and quality of data is paramount for the data analysis tools, modelling and optimization techniques to achieve their goals. In this context, the development of Digital Twins relies on having access to timely and accurate data.

As a DAFNI champion, I’m working on preparing and promoting DAFNI as a platform for Digital Twins. To that end, I’m implementing a small-scale Digital Twin using traffic data from the Sheffield area. The study uses real-time and historical data from 640 sensors to build a model for the traffic flow and predict the evolution of traffic in the next 15-30 minutes in locations of interest around the city. Given the large amount of data that needs to be stored and processed, the study makes great use of the existing capabilities of the DAFNI platform. In addition to testing the current capabilities, the study is also identifying new system requirements for the platform that are essential for the development of Digital Twins. Furthermore, the Sheffield Traffic Digital Twin will also make use of the DAFNI hardware that will soon be available at the University of Sheffield.

Another objective I have as a DAFNI champion is to contribute towards a Vision and Roadmap for Digital Twins which will help me identify core functionalities, architectures, underpinning technologies and standards of Digital Twins. These will translate into a new set of requirements for the DAFNI platform that will allow it to accommodate full-scale Digital Twins.

I’m honoured to be a DAFNI champion and I’m excited to work with the DAFNI team and to contribute to the development of the platform. I think the interest and the size of the research community on Digital Twins will significantly increase in the future and that DAFNI will play a central role in this by providing a platform for collaborative development, validation and implementation of Digital Twins for large-scale complex systems.