The reliance of military systems and armed forces on the EM spectrum creates vulnerabilities and opportunities for electronic warfare (EW) in support of military operations. EW is concerned with detecting, recognising then exploiting and countering the enemy's electronic order of battle, and calls for the development of innovative algorithmic solutions for information extraction and delivery of signals in contested electromagnetic environment. Traditionally, the subject of signal sensing/information extraction has been developed separately from the area of signal delivery. In contrast, this visionary project conducted at Imperial College London and University College London aims at leveraging the consortium complementary expertise in various areas of signal processing (sparsity, super-resolution and subspace methods, communications, radar, and machine learning) for civilian and defence applications to design and develop novel and innovative solutions for a cohesive treatment of information extraction and delivery of signals in contested electromagnetic environment. To put together this novel approach in a credible fashion, this project is organized in two major work packages. The first work package will analyze, separate and characterize signals across time, frequency, and space and extract useful information from those signals by developing and leveraging novel super-resolution, subspace and deep learning methods. The second work package will leverage progress made in the first work package and design signals and system responses for sensing and signaling in congested RF environments. Novel waveform design approaches will be derived for sensing using an extended ambiguity function-based framework, for precise spatiotemporal energy delivery using network-wide time-reversal and for joint sensing and signaling. Attention will also be drawn to the design of signals resilient to hardware and nonlinear channel responses. The project will be performed in partnership with academia/research institutes (University of Kansas, Fraunhofer) and industrial leaders in civilian and military equipment design and manufacturing (IBM, US Army Research Lab, Thales). The project demands a strong track record in a wide range of signal processing techniques and it is to be conducted by a unique research consortium with a right mix of theoretical and practical skills. With the above and given the novelty and originality of the topic, the research outcomes will be of considerable value to transform the future of electronic warfare and give the industry and defence a fresh and timely insight into the development of signal processing for contested electromagnetic environment, advancing UK's research profile in the world. Its success would radically change the design of electronic support measures, electronic coutermeasures and electronic counter-coutermeasures and have a tremendous impact on the defence sector and industry.

The ongoing COVID-19 epidemic requires careful monitoring as a variety of measures such as lockdown and social distancing are introduced and subsequently relaxed, leading to varying levels of demand for and capacity within the healthcare system. The disease has varying expected outcomes depending on the age, sex, and underlying comorbidities of cases. Epidemic dynamics, particularly in the presence of changing control policies, will shift the dominant modes of transmission and hence the distribution of disease. We will develop models to integrate the diverse but often noisy and incomplete datasets available, providing real-time policy support together with quantification of uncertainty. We will address three particular challenges. (1) Understanding spread in closely connected sub-populations in which there are close, repeated contacts capable of spreading disease such as households, hospitals, prisons, and care homes. Data from these contexts allow epidemiological parameters relating to infection risk conditional on contact to be identified in statistical work, and they are also important foci for policies. (2) Making short- and medium-term predictions of the epidemic trajectory and healthcare demand with appropriate uncertainty quantification. (3) Modelling long-term prospects for the epidemic, including the likelihood of eventual endemicity, the consequences of different virological assumptions about SARS-CoV-2, and how the different scenarios in this context will interact with long-term societal and health consequences of the pandemic. The project will use mathematical methodology, integrated with interdisciplinary expertise from social science, biology, clinical medicine, and epidemiology.

The United Nations' 17 Sustainable Development Goals (SDGs) aim to mobilise global efforts to 'transform our world' (UN, 2017) so as to address major challenges facing global society, such as achieving food security and nutrition for all (SDG 1, 2, 3, 8 &12). We will focus on India where agricultural sector which contributes more than 17.5% to its GDP, employs 250 million people and remains the backbone of India's rural population, which comprises almost 67% of the country's 1.3 billion population. Yet, most of India's farmers still remain under poverty. Merely 4% of India's food is moved through the cold chain compared to 70% in the UK, resulting in as much as 40% wastage, particularly in fresh fruits and vegetables, between farm and market. This reduces farmers' income, which in turn limits their capacity to invest and their incentive to grow more nutritious food. Whilst inadequate cold supply chain infrastructure results in large amount of wastage in fresh produce, inadequate value creation and the impact of climate change on agriculture productivity and food loss has led to increasing number of farmers suicide. Moreover, India has highest number of organic farmers globally but these farmers, who produce most of the country's high-value and high-nutrition foods, have little access to integrated cold chains. Indian farmers simply do not have financial resources to invest in precision agriculture and cold chain infrastructure development. With PM Modi's target of "doubling farmers' income by 2022", India necessitates a stronger case of technological intervention along with innovative business models and effective policies that double the income of farmers and maximise value for every stakeholder in the supply chain. The project TRANSSITioN will use a food systems approach to identify relevant STFC and indigenous technologies for digitising small-scale agriculture production, connecting farmers to supply chain, reducing food loss and managing food surplus. We will also identify relevant business and supply chain finance models supporting such technological interventions and ways in which different actors across the cold food chain could be engaged to directly and indirectly shape development outcomes. We will create "Sustainable Cold Food Chain Incubator Hub" (TRANSSITioN Hub) in India built on STFC ground breaking technologies from RAL Space (Thermal modelling, remote sensing, drone applications, Infrared Thermography), cryogenics from ASTeC and Cryox, data science capabilities (big data analytics, artifical intelligence) of STFC and IBM Research at Hartree Centre, along with interdisciplinary team from supply chain management, business sustainability, political science, food science, agriculture and material sciences, international research and stakeholder collaboration. The WPs will be applied to a set of two case studies starting from farms (organic and conventional) to consumption centre, co-identified with in-country partners. Hyderabad and Chennai region have been identified for the pilot project. Being host to companies such as such as Amazon, Flipkart, Jubilant Foods, Johnson & Johnson and Procter & Gamble, this region has become a consumer centric food logistics hub. With an established network of 50,000 organic farmers, processors, technology providers and retailers the selected region strongly aligns with the core competencies of our research agenda. Unfortunately, this region also had the second highest number of farmers suicide in 2016. Project TRANSSITioN, therefore, aims to forge a sustainable framework to meet different economic, social and commercial priorities of varied stakeholders to usher socio-economic change through value maximisation.

The United Nations' 17 Sustainable Development Goals (SDGs) aim to mobilise global efforts to 'transform our world' (UN, 2017) so as to address major challenges facing global society, such as achieving food security and nutrition for all (SDG 1, 2, 3, 8 &12). We will focus on India where agricultural sector which contributes more than 17.5% to its GDP, employs 250 million people and remains the backbone of India's rural population, which comprises almost 67% of the country's 1.3 billion population. Yet, most of India's farmers still remain under poverty. Merely 4% of India's food is moved through the cold chain compared to 70% in the UK, resulting in as much as 40% wastage, particularly in fresh fruits and vegetables, between farm and market. This reduces farmers' income, which in turn limits their capacity to invest and their incentive to grow more nutritious food. Whilst inadequate cold supply chain infrastructure results in large amount of wastage in fresh produce, inadequate value creation and the impact of climate change on agriculture productivity and food loss has led to increasing number of farmers suicide. Moreover, India has highest number of organic farmers globally but these farmers, who produce most of the country's high-value and high-nutrition foods, have little access to integrated cold chains. Indian farmers simply do not have financial resources to invest in precision agriculture and cold chain infrastructure development. With PM Modi's target of "doubling farmers' income by 2022", India necessitates a stronger case of technological intervention along with innovative business models and effective policies that double the income of farmers and maximise value for every stakeholder in the supply chain. The project TRANSSITioN will use a food systems approach to identify relevant STFC and indigenous technologies for digitising small-scale agriculture production, connecting farmers to supply chain, reducing food loss and managing food surplus. We will also identify relevant business and supply chain finance models supporting such technological interventions and ways in which different actors across the cold food chain could be engaged to directly and indirectly shape development outcomes. We will create "Sustainable Cold Food Chain Incubator Hub" (TRANSSITioN Hub) in India built on STFC ground breaking technologies from RAL Space (Thermal modelling, remote sensing, drone applications, Infrared Thermography), cryogenics from ASTeC and Cryox, data science capabilities (big data analytics, artifical intelligence) of STFC and IBM Research at Hartree Centre, along with interdisciplinary team from supply chain management, business sustainability, political science, food science, agriculture and material sciences, international research and stakeholder collaboration. The WPs will be applied to a set of two case studies starting from farms (organic and conventional) to consumption centre, co-identified with in-country partners. Hyderabad and Chennai region have been identified for the pilot project. Being host to companies such as such as Amazon, Flipkart, Jubilant Foods, Johnson & Johnson and Procter & Gamble, this region has become a consumer centric food logistics hub. With an established network of 50,000 organic farmers, processors, technology providers and retailers the selected region strongly aligns with the core competencies of our research agenda. Unfortunately, this region also had the second highest number of farmers suicide in 2016. Project TRANSSITioN, therefore, aims to forge a sustainable framework to meet different economic, social and commercial priorities of varied stakeholders to usher socio-economic change through value maximisation.

We urgently need proactive health support at the level of the general population: we have become, on average, an unhealthy nation. The new statistical norm is overweight to obese (60% of men and 49% of women). Co-related conditions from heart disease to type II diabetes, cost the NHS £48 Bn/year. Lack of sleep costs £40Bn. Stress costs £40Bn. 6% of our GDP goes to preventable "lifestyle conditions." Of the top 20 western nations, the UK ranks 18th or lower in QoL, Health, Wealth, Education and Democracy. Our productivity is 20% lower than the rest of the G7. While there is incredible optimism and investment in the potential benefits of ubiquitous, pervasive technology to help redress these conditions, digital health approaches to date have had low impact. This fellowship hypothesises that the lack of broad and sustained uptake of digital health technology is not a fault of the technology per se but with the range of models that inform how these technologies are designed. The current state of the art in digital health tech is (i) targeted at individuals although health practices are significantly influenced by social contexts; (ii) it assumes that given the right data we will make a rational decision to adopt a health practice without taking into account how the rest of our bodies - from our gut to our nervous system - is involved in decision processes (iii) the tools themselves can be antagonistic to rather than supporting of how the body works. E.g. a "smart alarm" that still disrupts sleep rather than finds ways to help us get sleep is antagonistic to our physiology which requires certain amounts of sleep to stay healthy. While current digital health technologies can and do work for some of the people some of the time, they have not been sufficient to deliver health in the complex contexts in which the UK lives and works. We need to develop better models to inform health tech design. This fellowship proposes to develop and test Inbodied Interaction (the alignment of health tech with how the body optimally performs) as a foundation to deliver and sustain personal and social Health Resilience: the capacity for individuals and their groups to build health knowledge, skills and practice to recover from and redress health challenges, from stress at home to shift changes at work. In line with EPSRC's challenge to "transform community health" by enabling better "self-management," digital interactive technologies must be aligned with how we work as organic-physical-cognitive-social complex systems. In respect of that model of "self" the fellowship will innovate on three strands of inbodied interaction technology: 1) Environment-Body Aligned: designing technology to support our physiology, from displays that help us maintain peripheral vision to stay more creative, to light use in VR lenses to improve cognitive performance. 2) Experience-to-Practice Aligned: to provide rapid access to the effects of better health experiences, and connect these with personally effective means to maintain these. 3) Group-to-Culture Aligned: to support groups identify and build more health resilient practices that work for their contexts. Thus "self-management" is transformed into our 3-level model of how this "self" is empowered by health tech in various contexts to create build and maintain "health." Through our co-design we will be engaging directly with hundreds of participants, and thousands more citizens virtually through our nation-wide Citizen Scientist web trials. We also have regular engagement with our expert advisory team representing industry, policy, and a range of disciplines. The Team is committed to help translate our work from project to practice, from policy to process, for transformational impact. By Fellowship end, we will have new digital health technologies and validated models for those tools to deliver Health Resilience for a Healthy Nation, and so help #makeNormalBetter@scale, for all.