Projects
Trustworthy digital infrastructure for identity systems
Enhancing the privacy and security of national digital identity systems
QUIPP – Quantifying utility and preserving privacy in synthetic data sets
Understanding the balance between utility, privacy and the uncertainty associated with synthetic data sets
Donating personal transactional data for research
Investigating the public acceptability of using commercial transactional data in public health research
People
Rafiah Patel
Enrichment Student
Teddy Cunningham
Enrichment Student
Professor Samuel Kaski
Turing Fellow
Maxine Mackintosh
Research Fellow
Professor Andrea Cavallaro
Turing Fellow
Dr Song Liu
Turing Fellow
Professor Andrew Dowsey
Turing Fellow
Dr Anya Skatova
Turing Fellow
Professor Ian Craddock
Turing FellowEvents
CIFAR-UKRI-CNRS AI & society: From principles to practice
Monday 03 Jun 2019 - Tuesday 04 Jun 2019
Time: 09:00 - 18:30
Publications and software
SecureABC: Secure antibody certificates for COVID-19
COVID-19 has resulted in unprecedented social distancing policies being enforced worldwide. As governments urgently...
Chris Hicks*, David Butler*, Carsten Maple, Jon Crowcroft. SecureABC: Secure AntiBody Certificates for COVID-19. CoRR, abs/2005.11833. 2020.
Differentially private health tokens for estimating COVID-19 risk
In the fight against Covid-19, many governments and businesses are in the process of...
David Butler*, Chris Hicks*, James Bell, Carsten Maple, Jon Crowcroft. Differentially Private Health Tokens for Estimating COVID-19 Risk. appeared in NDSS CoronaDef 2021.
Interest groups
Machine learning for radio frequency applications
How do we generate robust, real-time machine learning algorithms with integrated hardware and software for radio frequency applications?
AI in resource- and data-constrained environments
How can we build effective predictive models on hardware platforms that have limited computational resources and/or when the model training data are by definition always limited in amount?
