Treating older adults for medical conditions is complicated because they may need treatment for multiple conditions and they may also have chronic conditions such as reduced strength, mobility, hearing, eyesight or cognitive impairments such as dementia. This means hospital in-patient treatments may take longer and they may be unable to leave hospital to recover at home if they do not have a spouse/partner or family/friends/neighbours able to look after them. Older adults recovering at home frequently rely on 'circles of support' which range from relatives and neighbours, to the voluntary sector, social workers, paid carers, and medical professionals. The STRETCH project aims to help coordinate these circles of support with both wearable and smart home technologies to enhance the social and technical resilience of these circles of support. This should have the double benefit of increasing NHS capacity to cope with increasing numbers of older patients while improving care by making sure that medical professionals have timely and accurate information at all times about their patients. By having intelligently combined both the human and sensor-based sources of data, physicians will be able to recognize when a patient is deteriorating and intervene early to pre-empt problems or longer hospital stays.

Boundaries between digital technologies and ourselves become blurred as technology is integrated into our work, home and even our bodies. Interdisciplinary research is needed to understand how our sense of self - our psychological identity - affects and is affected by technology use. During this fellowship, I will lead an interdisciplinary team of psychologists and computer scientists to explore how our identity shapes and is shaped by technology in the fields of security and healthcare. This work will be underpinned by a programme of collaboration with industry partners, Polaris Consulting, the National Crime Agency (NCA), Dstl, Milton Keynes University Hospital (MKUH) and EDP Drugs and Alcohol Services to explore applications that support rather than replace human analysts and consultants. Sophisticated technologies are rapidly becoming part of our lives. Research on digital technology needs to urgently address concerns about privacy, trust, and ethical implications. I will extend current research in this area by considering how our different psychological identities shape what we find acceptable in different situations. For instance, a person might be less concerned about the tracking of personal information when thinking of themselves as a patient rather than as a parent. Throughout the fellowship, I will work closely with user groups (e.g., patients in the Lived Experience Group Exeter), industry partners and the general public to understand privacy concerns and privacy behaviour. I will also continue to develop the capacity to detect psychological identities from naturally occurring digital data (e.g., forum posts, blogs, e-mails). This research will allow us to understand which psychological identity (e.g., parent, addict, criminal network identity) is relevant in a particular situation. I will extend my current work to test whether it is possible to distinguish between several identities by analysing text data, whether detecting identities in text is robust to deception, and whether it is possible to tell how committed an individual is to their group from the way in which they communicate online. I will work closely with my industry partners, Polaris, NCA and Dstl, to explore how findings can enhance current machine learning capabilities and analytic approaches in defence and security. Finally, building on the identity detection work, I will examine how individuals develop new psychological identities (e.g., becoming a parent) and leave identities behind (e.g., leaving behind an addict identity during therapy), and the consequences of such transitions for mental health (e.g., post-natal depression, addiction recovery). I will work closely with industry partners MKUH and EDP to explore how these findings can be translated into diagnostic and monitoring solutions of the future that augment the work of therapists and medical consultants. The project will be integrated with research on software engineering through the EPSRC SAUSE platform grant. It will be conducted at the psychology department of the University of Exeter, which has a long and successful history of high-impact research. The project will draw on the strengths of the Social, Environmental and Organisational Psychology Research Group (SEORG), which is world-leading in research on social identity, privacy, and well-being, and the Clinical and Cognitive Research Groups, which are world-leading on depression and addiction. The University of Exeter also fosters interdisciplinary work, for instance through the co-supervision of EPSRC students across colleges, access to world-leading experts on machine learning and data science at the Alan Turing Institute and experts in healthcare at the Wellcome Centre for Cultures and Environments of Health and the EPSRC Centre for Predicitive Modelling in Healthcare. Taken together this project will establish Exeter as a key centre for EPSRC work on psychological identity and digital technologies.

In the last decade, the role of software engineering has changed rapidly and radically. Globalisation and mobility of people and services, pervasive computing, and ubiquitous connectivity through the Internet have disrupted traditional software engineering boundaries and practices. People and services are no longer bound by physical locations. Computational devices are no longer bound to the devices that host them. Communication, in its broadest sense, is no longer bounded in time or place. The Software Engineering & Design (SEAD) group at the Open University (OU) is leading software engineering research in this new reality that requires a paradigm shift in the way software is developed and used. This platform grant will grow and sustain strategic, multi-disciplinary, crosscutting research activities that underpin the advances in software engineering required to build the pervasive and ubiquitous computing systems that will be tightly woven into the fabric of a complex and changing socio-technical world. In addition to sustaining and growing the SEAD group at the OU and supporting its continued collaboration with the Social Psychology research group at the University of Exeter, the SAUSE platform will also enable the group to have lasting impact across several application domains such as healthcare, aviation, policing, and sustainability. The grant will allow the team to enhance the existing partner networks in these areas and to develop impact pathways for their research, going beyond the scope and lifetime of individual research projects.

Imagine a future where autonomous systems are widely available to improve our lives. In this future, autonomous robots unobtrusively maintain the infrastructure of our cities, and support people in living fulfilled independent lives. In this future, autonomous software reliably diagnoses disease at early stages, and dependably manages our road traffic to maximise flow and minimise environmental impact. Before this vision becomes reality, several major limitations of current autonomous systems need to be addressed. Key among these limitations is their reduced resilience: today's autonomous systems cannot avoid, withstand, recover from, adapt, and evolve to handle the uncertainty, change, faults, failure, adversity, and other disruptions present in such applications. Recent and forthcoming technological advances will provide autonomous systems with many of the sensors, actuators and other functional building blocks required to achieve the desired resilience levels, but this is not enough. To be resilient and trustworthy in these important applications, future autonomous systems will also need to use these building blocks effectively, so that they achieve complex technical requirements without violating our social, legal, ethical, empathy and cultural (SLEEC) rules and norms. Additionally, they will need to provide us with compelling evidence that the decisions and actions supporting their resilience satisfy both technical and SLEEC-compliance goals. To address these challenging needs, our project will develop a comprehensive toolbox of mathematically based notations and models, SLEEC-compliant resilience-enhancing methods, and systematic approaches for developing, deploying, optimising, and assuring highly resilient autonomous systems and systems of systems. To this end, we will capture the multidisciplinary nature of the social and technical aspects of the environment in which autonomous systems operate - and of the systems themselves - via mathematical models. For that, we have a team of Computer Scientists, Engineers, Psychologists, Philosophers, Lawyers, and Mathematicians, with an extensive track record of delivering research in all areas of the project. Working with such a mathematical model, autonomous systems will determine which resilience- enhancing actions are feasible, meet technical requirements, and are compliant with the relevant SLEEC rules and norms. Like humans, our autonomous systems will be able to reduce uncertainty, and to predict, detect and respond to change, faults, failures and adversity, proactively and efficiently. Like humans, if needed, our autonomous systems will share knowledge and services with humans and other autonomous agents. Like humans, if needed, our autonomous systems will cooperate with one another and with humans, and will proactively seek assistance from experts. Our work will deliver a step change in developing resilient autonomous systems and systems of systems. Developers will have notations and guidance to specify the socio-technical norms and rules applicable to the operational context of their autonomous systems, and techniques to design resilient autonomous systems that are trustworthy and compliant with these norms and rules. Additionally, developers will have guidance to build autonomous systems that can tolerate disruption, making the system usable in a larger set of circumstances. Finally, they will have techniques to develop resilient autonomous systems that can share information and services with peer systems and humans, and methods for providing evidence of the resilience of their systems. In such a context, autonomous systems and systems of systems will be highly resilient and trustworthy.