Medicine is undergoing a simultaneous shift at the levels of the individual and the population: we have unprecedented tools for precision monitoring and intervention in individual health, and we also have high-resolution behavioural and social data. Precision healthcare seeks to deploy therapies that are sensitive to the particular genetic, lifestyle and environmental circumstances of patients. Understanding how best to use these numerous features about individual patients is a true mathematical challenge. The EPSRC Centre for Mathematics of Precision Healthcare at Imperial serves as a focal point by linking up mathematical, computational and medical capabilities at Imperial around the theme of multi-scale networks for data-rich precision healthcare. You can read more here ...

A new research initiative bringing together world-renowned Imperial academics working on the safety and security of our modern software systems. The SaSsy Initiative is a new Imperial-X research institute, bringing together world-renowned Imperial academics working on the safety and security of our modern software systems, underpinned by rigorous design, specification, testing and verification. Traditional methods for ensuring the correctness and reliability of our software systems, such as informal prose specification and ad-hoc validation, are no longer adequate for our modern software systems. The SaSSy academics work on novel techniques and tools that can provide trust in our systems, in the deep technical sense of principled design, mathematical specification, systematic testing and formal verification, which are vital not only to making our systems safe and secure, but also to give stability to our international software infrastructure. Our research has come of age: our mathematical techniques are tractable; our tools are well-engineered; and our work is used in applications ranging from autonomous vehicles and multi-agent systems, to software development, standards and infrastructure, to embedded systems and low-energy hardware. The purpose of the SaSSy Initiative is to bring rigorous, scientific methods to the design and analysis of our modern software systems, to set new standards of rigour and propose new ways to validate emerging AI-driven systems which are not catered for by current approaches. The SaSSy Initiative is loosely grouped under the research themes Safe AI, Trustworthy Software, Architectural Foundations, and Security. This initiative is led by Professor Phillipa Gardner. You can read more here ...

Our centre is dedicated to using AI to disrupt and advance Science, Engineering and Mathematics and is underpinned by core support from Schmidt Sciences. You can read more here ...

XAI has witnessed unprecedented growth in both academia and industry in recent years (alongside AI itself), given its crucial role in supporting human-AI partnerships whereby (potentially opaque) data-driven AI methods can be intelligibly and safely deployed by humans in a variety of settings, such as finance, healthcare and law. XAI is positioned at the intersection of AI, human-computer interaction,  the social sciences (and in particular psychology) and applications. XAI has caught the attention of legislators and policy makers, amongst others (e.g. XAI is part of the AI sector deal focus and the ICO conducted in 2020 a consultation with industry regarding guidance on XAI; and GDPR can be interpreted as sanctioning a “right to explanation” for algorithmic decision-support, e.g. in credit lending decisions). Overall, XAI is increasingly part of all AI policies on ethics, trustworthiness and safety of AI. This XAI research centre covers the full spectrum across methodologies for explanation for various AI methods, human-computer interaction, the social sciences and applications in healthcare, finance and the law, with a particular emphasis on interactive (included conversational) exchanges between humans and AI-empowered machines. You can read more here ...

StatML is a EPSRC funded Centre for Doctoral Training in Statistics and Machine Learning. The StatML CDT is a cohort-based doctoral programme based at Imperial College London and University of Oxford. The Statistics and Machine Learning programme is a four-year PhD/DPhil research programme (or longer if studying part-time). It trains the next generation of researchers in statistics and statistical machine learning, who will develop widely-applicable novel methodology and theory and create application-specific methods, leading to breakthroughs in real-world problems in government, medicine, industry and science. You can read more here ...