Press Releases
Fifty new planets confirmed in machine learning first
Fifty potential planets have had their existence confirmed by a new machine learning algorithm developed by University of Warwick scientists.
Warwick Academic helping to inform London's response to Covid-19 lockdown
Dr Theo Damoulas, associate Professor in Data Science at the University of Warwick and Deputy Programme Director for the Turing’s Data-centric Engineering programme is working with GLA, TfL, Microsoft and other Universities to help inform London's response to the Covid-19 lockdown in a project called "Odysseus", which aims to understand 'London's busyness'.
Food prices after a hard Brexit could increase by £50 per week
A hard Brexit could result in a family of four seeing their food prices increase to up to £50.98 per week researchers at the University of Warwick have found. If we leave with a deal the increase could be as little as £5.80 per week, or £18.17.
Warwick opens its doors for another science extravaganza
Fancy tasting ice cream made with liquid nitrogen, building a wind turbine or dancing like a sound wave? Youngsters with a passion for science will be able to enjoy some real-life experiments at the University of Warwick’s Science Gala next week.
Infectious diseases to be detected and prevented thanks to £4m grant
Infectious diseases could be detected, prevented and controlled thanks to a new £4m grant from the NIHR to the University of Warwick. Researchers will work with partners to develop the use of cutting edge genomics to protect public health.
London air to be kept clean thanks to Warwick researchers
Researchers will build on their existing work on air quality and simulation-based inference to revolutionise pollution forecasting by combining modern machine learning and statistical methodology.
The project will develop and utilise computational techniques based around the simulation of large ensembles of “particles” to allow us to estimate and quantify our uncertainty. These techniques will be combined with models inspired by modern machine learning, particularly utilising deep Gaussian processes to describe the profile of atmospheric pollutants as they evolve over time.