Data-centric engineering

The next decade will see step changes in data-driven technology, impacting all aspects of engineering and industry. In preparation the Lloyd’s Register Foundation and The Alan Turing Institute have partnered on a major initiative in data-centric engineering.

Lloyds RThis programme, funded by the Lloyd’s Register Foundation, is performing fundamental research and ground-breaking innovation in the applications of data science to engineering. We are directly addressing the challenges in improving resilience in infrastructure and safety in society, and developing scientific advances that will have international impact for years to come.

Professor Mark Girolami FRSE (Dept. of Mathematics at Imperial College London) has been appointed to establish, develop and lead the research activities. The programme will be located and run at The Alan Turing Institute headquarters in the British Library, with a portion of the funding allocated to a collaboration with Imperial College London, who will bring in their researchers to work alongside Turing Fellows to support the delivery of the programme’s core activities.

Professor Mark Girolami

Professor Mark Girolami, Programme Director, says, ‘“I am delighted to join the Turing-Lloyd’s Register Foundation team as Programme Director, and I look forward to defining, building, and leading the international programme on data-centric engineering.”

Grand Challenges

The programme will identify Grand Challenges for research, development, and their translation to deployed solutions. It also seeks partners to help develop the future aims of the programme.

The Grand Challenges being developed are:

1. Resilient and Robust Infrastructures

There is widespread, growing availability of heterogeneous data arising from major complex infrastructure systems such as cities, railways, industrial plant, ships, road networks and supply chains.  These systems are characterised by multiple human and technological interfaces and provide an opportunity to make a step-change in our ability to provide robust protocols for a wide variety of engineering design issues. The grand challenge underlying this goal is to develop algorithms with the capability of optimally blending data with models in a manner which takes into account uncertainty in both.

2. Monitoring Safety of Complex Engineering Systems

Safety is a critical concern in the design and operation of countless engineered systems, ranging from aircraft engines and aerospace structures to vehicle electrical systems and even software. Understanding and anticipating the impact of rare and high-consequence events in these systems is then an essential task.  Research and development activities are also tied to questions of health monitoring and predictive maintenance, wherein by learning the state and the failure propensity of a system, users can carefully target repairs, modify operational envelopes, and make quantitative assessments of risk.

3. Data-Driven Engineering Design under Uncertainty

We are addressing fundamental questions at the intersection of data and optimization: (i) optimal design under uncertainty, with particular attention to the management of risk; (ii) optimal experimental design, yielding efficient and targeted strategies for sensing and for identifying the most valuable elements of large and heterogeneous data sets; and (iii) optimal data collection for design optimization, closing the loop between the design of engineered systems and the acquisition of data to inform these designs. Advances in these areas will impact engineering design across the entire spectrum of target applications described above, from aerospace to energy systems and critical infrastructure.

Advisory Board

Professor Muffy Calder OBE FREng FRSE FBCS

Professor Lord Mair CBE FREng FRS

Professor Sir David John Spiegelhalter, OBE FRS

Strategic Leaders

Prof Axel Gandy

Prof Axel Gandy

Prof Julie McCann

Prof Julie McCann

Prof Aleksandar Mijatović

Prof Aleksandar Mijatović

 

 

 

 

 

 

Group Leaders

Dr Weisi Guo

Dr Weisi Guo

Dr Franz Kiraly

Dr Din-Houn Lau

Dr Din-Houn Lau

Dr Chris Oates

Dr Chris Oates

 

 

 

 

 

 

Dr Catalina Vallejos

Dr Catalina Vallejos

Dr Sebastian Vollmer

Dr Sebastian Vollmer

Dr Ricardo Silva

Dr Ricardo Silva

 

 

 

 

 

 

 

Related Research Projects

 

Current Opportunities

Lloyd's Register Foundation's Foresight Review of Big Data

Read the Lloyd’s Register Foundation’s Foresight Review of Big Data

We are keen to engage with both industry and partners with challenges whose solution is reliant on data-centric engineering, as well as researchers working internationally on the development of new ideas. If you would like to be involved please contact:

Darren Grey

Programme Manager
dgrey@turing.ac.uk
+44 (0)203 862 3309