A machine learning revolution in disaster response Turing researchers have combined crowd-sourcing, machine learning and neural networks to rapidly reveal the many dimensions of natural disasters, deploying the technology in the aftermath of Hurricane Dorian
Co-designing computing High-performance computing (HPC) environments such as data centres can be ill-equipped to deal with data science tasks, so Turing researchers collaborated with Intel to co-design better architecture for their HPC systems
Towards a greener grid Turing researchers and doctoral students contributed to a new solar forecasting system for National Grid, which is 33% more accurate at day-ahead forecasts, aiding in more efficient balancing of supply and demand and lowering consumer costs
Augmenting clinical decision-making Working with the Cystic Fibrosis Trust, Turing researchers have been developing machine learning methods that could dramatically improve the accuracy of clinical assessments of people with cystic fibrosis
Understanding urban air quality Turing researchers are working with the Greater London Authority to use machine learning and statistical methodology to better analyse air pollution sensor data, design better policy interventions, and improve urban quality of life
Making simulations simpler Software engineers at the Turing, in collaboration with partners at Imperial College and UCL, have developed a user interface which aims to make running simulations more user-friendly, for both academic and industrial communities
Fairer algorithm-led decisions Turing researchers from diverse fields have produced a new way of approaching fairness in algorithm-led decisions, by looking at the causes of certain factors that can often result in biased decision-making
A right to explanation Advice from Turing researchers, urging the need for individuals to have a legally binding right to have automated decisions made about them explained, is helping shape how the new EU data protection regulations will be implemented