Trustworthy digital infrastructure for identity systems Enhancing the privacy and security of national digital identity systems
Optimising hypertension management strategies Using smart algorithms to optimise treatment decisions in blood pressure management and reduce economic burden on healthcare providers
Visual diagnostics for Markov Chain Monte Carlo (MCMC) Designing visual diagnostics that articulate the concepts underlying robust MCMC computational algorithms
The (mis)informed citizen Using computational approaches to evaluate the quality of online news and studying its impacts
Security and privacy in the decentralised web Developing techniques to understand and model users and infrastructure in the decentralised web
Automated discrimination in internet filtering Using machine learning to identify discrimination in the choice of websites blocked by internet service providers and government
Critical infrastructures as a control system Developing smart data communication protocols to achieve robustness and resilience of complex critical infrastructures
Retrofit design in the built environment Exploring decision making processes common in construction and building management, to evaluate potential opportunities for retrofitting in the built environment
Probabilistic Value-Deviation-Bounded Integer Codes for Approximate Communication When computing systems can tolerate the effects of errors or erasures in their communicated... Stanley-Marbell, Phillip, and Paul Hurley. "Probabilistic value-deviation-bounded integer codes for approximate communication." arXiv preprint arXiv:1804.02317 (2018)
BEIS and DCMS consultation on Smart Data Consultation In 2018, the Department for Business, Energy and Industrial Strategy (BEIS) published its...
The Turing’s Finance and Economics Programme responds to the Smart Data consultation Three things you need to know Thursday 08 Aug 2019
UK multi-agent systems symposium Monday 24 Feb 2020 Time: 10:00 - 17:00 Edward Hughes Yoram Bachrach Sam Devlin Subramanian Ramamoorthy Victoria Mico Egea
Data science for bridging the digital divide and beyond Tuesday 16 Jul 2019 - Wednesday 17 Jul 2019 Time: 10:00 - 17:00
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
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?
Environment and sustainability What role can data science and AI play in addressing the challenges associated with environmental change?