Modern society faces a fundamental problem: the reliability of complex, evolving software systems on which it critically depends cannot be guaranteed by the established, non-mathematical techniques, such as informal prose specification and ad-hoc testing. Modern companies are moving fast, leaving little time for code analysis and testing; concurrent and distributed programs cannot be adequately assessed via traditional testing methods; users of mobile applications neglect to apply software fixes; and malicious users increasingly exploit programming errors, causing major security disruptions. Trustworthy, reliable software is becoming harder to achieve, whilst new business and cyber-security challenges make it of escalating importance. Developers cope with complexity using abstraction: the breaking up of systems into components and layers connected via software interfaces. These interfaces are described using specifications: for example, documentation in English; test suites with varying degrees of rigour; static typing embedded in programming languages; and formal specifications written in various logics. In computer science, despite widespread agreement on the importance of abstraction, specifications are often seen as an afterthought and a hindrance to software development, and are rarely justified. Formal specification as part of the industrial software design process is in its infancy. My over-arching research vision is to bring scientific, mathematical method to the specification and verification of modern software systems. A fundamental unifying theme of my current work is my unique emphasis on what it means for a formal specification to be appropriate for the task in hand, properly evaluated and useful for real-world applications. Specifications should be validated, with proper evidence that they describe what they should. This validation can come in many forms, from formal verification through systematic testing to precise argumentation that a formal specification accurately captures an English standard. Specifications should be useful, identifying compositional building blocks that are intuitive and helpful to clients both now and in future. Specifications should be just right, providing a clear logical boundary between implementations and client programs. VeTSpec has four related objectives, exploring different strengths of program specification, real-world program library specification and mechanised language specification, in each case determining what it means for the specification to be appropriate, properly evaluated and useful for real-world applications. Objective A: Tractable reasoning about concurrency and distribution is a long-standing, difficult problem. I will develop the fundamental theory for the verified specification of concurrent programs and distributed systems, focussing on safety properties for programs based on primitive atomic commands, safety properties for programs based on more complex atomic transactions used in software transactional memory and distributed databases, and progress properties. Objective B: JavaScript is the most widespread dynamic language, used by 94.8% of websites. Its dynamic nature and complex semantics make it a difficult target for verified specification. I will develop logic-based analysis tools for the specification, verification and testing of JavaScript programs, intertwining theoretical results with properly engineered tool development. Objective C: The mechanised specification of real-world programming languages is well-established. Such specifications are difficult to maintain and their use is not fully explored. I will provide a maintainable mechanised specification of Javascript, together with systematic test generation from this specification. Objective D: I will explore fundamental, conceptual questions associated with the ambitious VeTSpec goal to bring scientific, mathematical method to the specification of modern software systems.

This project is about devising and implementing a smart operating room environment, powered by trustable, human-understanding artificial intelligence, able to continually adapt and learn the best way to optimise safety, efficacy, teamwork, economy, and clinical outcomes. We call this concept MAESTRO. A fitting analogy for MAESTRO is that of an orchestra conductor, a 'maestro', who oversees, overhears and directs a group of people on a common task, towards a common goal: a masterful musical performance. Although the music score is identical for all orchestras, there is no doubt that they all perform it in different ways and some significantly better than others. Although the quality and personality of orchestra musicians is very important, it is widely accepted that the role of the maestro is crucial, and extends beyond the duration of the musical performance to rehearsals and understanding of the context behind the music score. Thus, while it is possible for orchestras to perform without conductors, most cannot function without one. Our proposed MAESTRO AI-powered operating room of the future rotates around four key elements: (a) The holistic sensing of patient, staff, operating room environment and equipment through an array of diverse sensor devices. (b) Artificial intelligence focused on humans (human-centric), able to continually understand situations and actions developing in the operating room, and of intervening when necessary. (c) The use of advanced human-machine user interfaces for augmenting task performance. (d) A secure device interconnectivity platform, allowing the full integration of all above key elements. As in our orchestra analogy, our envisioned MAESTRO directs the OR staff and surgical devices before, during and after a surgical procedure by: (1) Sensing surgical procedures in all their aspects, including those which are currently neglected such as the physiological responses of staff (e.g., heart rate, blood pressure, sweating, pupil dilation), focus of attention, brain activity, as well as harmful events that may escape the attention of the clinical team. (2) Overseeing individual and team performance in real-time, throughout the operation and across different types of surgeries and different teams. (3) Guiding and assisting the surgical team via automated checkpoints, virtual and augmented visualisations, warnings, individualised and broadcasted alerts, automation, semi-automation, robotics, and other aids and factors that can affect performance in the operating room. (4) Augmenting and optimising individual and collective operational capabilities, skills, and task ergonomics, through novel human-machine interaction and interfacing modalities. The project is designed to have a significant societal, economic and technological impact, and to establish the NHS as a leading healthcare paradigm worldwide. MAESTRO leverages the expertise of top researchers in the areas of robotics, sensing, artificial intelligence, human factors, health policies and patient safety. It is co-designed in collaboration with top clinicians, one of the largest NHS Trusts in England, patient groups, performing artists, and several small and medium-sized enterprises and large multinational industries operating in the areas of artificial intelligence, medical devices, digital health, large networks, cloud services, cyber security.

Clinicians, patients and policy makers lack access to accurate, real time information on new treatments for treating cancer. This is because such a large amount of information is continuously generated, and it is too complicated to be manually analysed in a timely fashion. This is sometimes referred to as a health 'infodemic'. Information analysed to create clinical evidence (known as systematic reviews) quickly goes out of date, and national bodies responsible for appraising new treatments such as the National Institute for Clinical Excellence are unable to keep up. It is increasingly hard to detect misinformation published within medical literature, and an increasing number of papers have to be withdrawn after publication. INDICATE is a deep learning tool for the autonomous generation of systematic reports and analysis of both structured and unstructured data from published literature on cancer. It has been developed through a collaboration between Imperial College London and Amazon Web Services, NICE and the British Medical Journal (BMJ). The aim is to develop a methodology for the real time analysis of healthcare infodemics that can be used to autonomously create clinical guidance and identify misinformation. This project will build on previous work to develop AI methodologies that automate how we search for medical literature and it will intelligently support peer reviewers as they appraise and assess the quality of research papers. This work has three main goals: 1. To develop a tool for detecting research fraud. 2. To asses if our AI tools can speed up the creation of NICE guidance. 3. To develop autonomous summary reports of clinical evidence of breast cancer treatment that could be used by medical publishers. The study group will work with clinicians, researchers and NICE to define and prioritise critical questions that require answering and to refine the user interface for the system. Moreover, we will prospectively validate the performance of the system to determine the accuracy and performance of its reporting mechanism. The validated data generated by this study will form the basis of a phase II study that scales the number of cancer types and the trial of the technology in a real world clinical environment.

The Digital Health Hub for Antimicrobial Resistance (AMR) aims to harness innovative digital technologies to ultimately transform antimicrobial one-health surveillance and antimicrobial stewardship, recognising the interconnectedness of AMR between humans, animals and the environment. The World Health Organization declared AMR - also known as the 'silent pandemic' - a top 10 global public health threat facing humanity. AMR also ranks on the UK Cabinet Office Risk Register and yet despite this recognition, there remains alarmingly low levels of attention and funding for AMR prevention. The 2016 O'Neill Review on Antimicrobial Resistance highlights that by 2050, 10 million lives a year and a cumulative US$100 trillion of economic output are at risk unless action is taken to reduce AMR. Resistant pathogens from animals, humans and food can be cross-transmitted and environmental reservoirs are a potentially important domain in which the mobilisation and transfer of resistant genes occur. Thus, an integrated One Health approach to AMR surveillance and public health action is needed. Moreover, there is growing concern that climate change could increase the risk of emerging and re-emerging infectious diseases. There is growing recognition of the importance of data science and digital health technologies in the fight against AMR, though the field remains in its infancy. The COVID-19 pandemic has dramatically accelerated advances in digital health technologies, driven by unprecedented need, and there is a huge opportunity to leverage these advances for AMR. However, there remain many challenges: poor understanding of one-health needs; data linkage, silos and gaps hinder surveillance; the lack of rapid tests, the lack of public awareness of AMR; digital interventions often do not prioritise user-led design and are not grounded in behaviour change; data privacy, security and ethical issues of bringing together large datasets; health inequalities and the digital divide; the disconnect between early stage research and AMR needs, and lack of understanding of how digital technologies can be commercialised, regulated and integrated into health systems and patient pathways. The Digital Health Hub for AMR brings together a critical mass of Co-Is working across traditional disciplines for AMR, including computer science, biomedical engineering, behavioural social science, environmental science, data visualisation, and clinical and public health research, from five universities, NHS, UK Health Security Agency, Centre for Ecology and Hydrology, charities and industry partners. Our hub vision will be achieved through five objectives: 1. Systems-level needs: To nurture a new culture of cross-sector engagement to accelerate the creation and adoption of digital health innovations for AMR one-health surveillance and antimicrobial stewardship. 2. Skills and Capacity: To grow interdisciplinary skills, capacity, knowledge sharing and leadership needed to deliver a world-leading digital health strategy for combatting AMR. 3. Grand Challenges: To co-create digital health solutions for two AMR grand challenges: i) Digital one-health surveillance of antibiotic use and AMR, linking human, animal and environmental data ii) Digital antimicrobial stewardship via decision support algorithms, digital diagnostics wearables and sensors 4. Partnership Fund: To grow critical mass and a hub of innovation by seeding interdisciplinary pilot studies between industry, academia, health and social care. 5. Impact and Engagement: To maximise hub impact and EPSRC's investment through our communications strategy, patient and public engagement, biannual conferences and events.

The Northern Health Futures (NortHFutures) hub aims to create a world-leading healthcare technology (health-tech) development ecosystem. This will address unmet health needs and inequalities by supporting: inclusive digital skills training and sharing; research, innovation and entrepreneurship, enabled by digital design. Based in the North East and North Cumbria (NENC), with national and global reach, NortHFutures will support underserved communities, as it is known that national disparity of investment in NENC negatively impacts population health and wellbeing, and that a 'levelling up' of investment is needed to stimulate socio-economic and cultural growth for all, to encourage living and ageing well. NortHFutures builds upon the joined-up NENC approach to people-powered digital health innovation, as our regional Integrated Care Board (ICB) uniquely involves local authorities, communities, and citizens. Academic team members have a research track record that is stakeholder-involved and civic- and community-engaged. They are world-leading on understanding (i) health inequalities from medical, social, and design perspectives, and (ii) the opportunities for enrichment and enablement related to ageing well, connecting rural and urban populations, and pioneering applications of data science. In the pilot phase, we draw on this specialist expertise to address evidenced unmet health needs in NENC, (which have national and global importance): children and young people's health and nutrition; mental health and wellbeing; development of digital surgical pathways (for monitoring patient journeys beyond the hospital); living well with multiple long-term conditions. We combine the strengths and resources of 6 universities (Newcastle, Cumbria, Durham, Northumbria, Sunderland and Teesside), bringing regional investment in NIHR services, facilities and Applied Research Collaborations, plus National Innovation Centres for Ageing (NICA), Data (NICD) and Rural Enterprise (NICRE), National Horizons Centre (NHC), EPSRC Digital Economy programmes in data and digital citizens, and Health Data Research UK, the UK's national institute for health data science. NortHFutures supports new planned Centres, including Northumbria's Centre for Health & Social Equity and Cumbria's new campus and medical school. These University offers combine with an extensive partner network, including: ICB-NENC, 7 NHS Trusts, NHS Business Services Authority, Department of Health and Social Care, Health Education England; VCSE organisations delivering community-based services; industry partners - from SMEs to global tech giants; civic bodies such as Local and Combined Authorities; existing health research networks (e.g. AHSN-NENC, Newcastle Health Innovation Partnership); and innovation accelerators (e.g. Innovation SuperNetwork). Through an integrated, regional approach uniting this consortium for the first time, NortHFutures ambitiously aims to establish global leadership in Digital Health. To deliver this we will develop a supportive community infrastructure. We will co-design a digital brokerage service to connect and amplify partners' work, to offer and consume expertise, services and facilities (supporting acceleration of health-tech companies at differing tech-readiness levels). We will pioneer a Live Digital Health Databank, to explore, and train for, advanced healthcare data analytics, combining live data flows with care records (e.g. Great North Care Record). This will support personalised health diagnostics and interventions, giving our hub a unique value proposition to companies wishing to explore advanced data technologies. We will invest in Extended Reality pilots, to open up possibilities for clinical practice and service delivery. Our approaches will embed Responsible Research and Innovation (RRI), and Patient and Public Engagement (PPIE) throughout, to deliver health-tech that supports care beyond the hospital and is co-designed with end-users.