DATA-CENTRIC: Developing AccounTAble Computational ENgineering Through Robust InferenCe (2018 - 2021)
The aim of this EPSRC fellowship is to develop algorithms that are accountable. This means algorithms capable of quantifying the uncertainty arising from computation itself, delivering simulations that are more transparent, traceable and at the same time more efficient. Numerical computations in industry (and hence the models that depend on them) suffer from an inevitable loss of accuracy due to: a) time and cost constraints of running modern high-fidelity computer models, b) simplifying approximations necessary to translate mathematical models into computational models, and c) limited numerical precision inherent to any computer system. Therefore, there is a continuous risk of relying on unverified computational evidence, and the path from modelling to decision-making can be (inadvertently or unwillingly) obscured by the lack of accountability.
DATA-CENTRIC works under the framework of Probabilistic Numerics, an emerging research area that enables decision-makers to monitor, diagnose and control the quality of computer simulations. Probabilistic Numerics treats computation as a statistical problem, thus enriching computation with a probabilistic measure of numerical error. This idea is gathering momentum, especially in the UK. However, theoretical development are still in their early stages and except for a few examples, it has not been applied to solve large-scale industrial problems. Consequently, it has not yet been adopted by industry. DATA-CENTRIC aims at bridging this gap. In particular, it will produce new solutions to industrial problems in Biomechanics and Robust Design. This has the potential of transforming personalised medicine and high-value manufacturing and will open the door to new industrial applications.