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COVID-19: genetic network analysis provides ‘snapshot’ of pandemic origins

Study charts the 'incipient supernova' of SARS-CoV-2 through genetic mutations as it spread from China and Asia to Australia, Europe and North America. Researchers say their methods could be used to help identify undocumented infection sources.

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150 scientists from new institute join Cambridge fight against COVID-19

One of Cambridge’s newest institutes, established to study the relationship between infectious disease and our immune systems, is leading the University of Cambridge’s response to the COVID-19 pandemic, with over 150 scientists and clinicians, the UK’s largest academic Containment Level 3 Facility, and a range of...

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Interactive tool shows the science behind COVID-19 control measures

An online tool to illustrate the effects of different COVID-19 control measures has been developed by a team of University of Cambridge researchers.

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Researcher profile: Professor Julia Gog

Professor Julia Gog is a mathematician who specialises in modelling the spread of infectious diseases, particularly pandemic influenza. For months, she and the other members of her research group in the Department of Applied Mathematics and Theoretical Physics have been modelling and mapping the spread of coronavirus and...

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AstraZeneca/GSK/University of Cambridge collaborate to support UK national effort to boost COVID-19 testing

As part of the UK Government’s announcement of a new five pillar plan to boost testing for COVID-19, AstraZeneca, GSK and the University of Cambridge have formed a joint collaboration to take action to support this national effort.

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Cambridge engineers use industrial modelling techniques to help Addenbrooke’s manage COVID-19 care

Modelling tools originally designed to improve the efficiency of factories are being used by Cambridge engineers to help Addenbrooke’s Hospital manage the COVID-19 emergency.

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Cambridge engineers use industrial modelling techniques to help Addenbrooke’s manage COVID-19 care

Modelling tools originally designed to improve the efficiency of factories are being used by Cambridge engineers to help Addenbrooke’s Hospital manage the COVID-19 emergency.

Read full article on cam.ac.uk site

New app collects the sounds of COVID-19

A new app, which will be used to collect data to develop machine learning algorithms that could automatically detect whether a person is suffering from COVID-19 based on the sound of their voice, their breathing and coughing, has been launched by researchers at the University of Cambridge.

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AI techniques used to improve battery health and safety

Researchers have designed a machine learning method that can predict battery health with 10x higher accuracy than current industry standard, which could aid in the development of safer and more reliable batteries for electric vehicles and consumer electronics.

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Progress using COVID-19 patient data to train machine learning models for healthcare

Following from last week's call for governments to use machine learning and AI techniques to help in the fight against the COVID-19 pandemic, Professor Mihaela van der Schaar gives an update on a working proof of concept she has built using anonymised data from Public Health England.

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