People involved in trying to find missing persons have to depend upon images of them taken before they disappeared. For missing adults, this is not too great a problem, as their appearance will not have changed radically. However, children may have changed out of all recognition. The aim of this project is to develop a way of 'ageing' a facial image to give a realistic impression of what the missing child will look like now. If successful, the system will be a major boost to the work of those locating missing children: it will provide accurate images rapidly and simply at a fraction of the current cost.The project will develop algorithms, or step-by-step problem-solving procedures, that can be used to age a facial image. These will be based on studies of facial variation in children over two critical stages in their development which will be undertaken at Dundee University, and from existing face data archives held at the University of Kent. The project will benefit from having very close interaction and guidance from the National Missing Persons Helpline (NMPH) and VisionMetric, a company that has a good deal of commercial experience in developing forensic imaging applications.The final outcome of the project will be a software system that can be used on standard hardware and over the Internet. To get to this stage, however, there will be a series of project stages:Compiling and annotating a photographic database of children's faces spanning two main developmental phases (at Dundee)Developing a comprehensive statistical model of facial appearance (at Kent)Developing person-specific age transformation techniques (at Dundee and Kent)Developing these techniques to make them quick and user-friendly, so that they can be used for practical or commercial development (at Kent)Practical implementation of the software system (at Kent, involving VisionMetric, NMPH and the Metropolitan Police)

People involved in trying to find missing persons have to depend upon images of them taken before they disappeared. For missing adults, this is not too great a problem, as their appearance will not have changed radically. However, children may have changed out of all recognition. The aim of this project is to develop a way of 'ageing' a facial image to give a realistic impression of what the missing child will look like now. If successful, the system will be a major boost to the work of those locating missing children: it will provide accurate images rapidly and simply at a fraction of the current cost.The project will develop algorithms, or step-by-step problem-solving procedures, that can be used to age a facial image. These will be based on studies of facial variation in children over two critical stages in their development which will be undertaken at Dundee University, and from existing face data archives held at the University of Kent. The project will benefit from having very close interaction and guidance from the National Missing Persons Helpline (NMPH) and VisionMetric, a company that has a good deal of commercial experience in developing forensic imaging applications.The final outcome of the project will be a software system that can be used on standard hardware and over the Internet. To get to this stage, however, there will be a series of project stages:Compiling and annotating a photographic database of children's faces spanning two main developmental phases (at Dundee)Developing a comprehensive statistical model of facial appearance (at Kent)Developing person-specific age transformation techniques (at Dundee and Kent)Developing these techniques to make them quick and user-friendly, so that they can be used for practical or commercial development (at Kent)Practical implementation of the software system (at Kent, involving VisionMetric, NMPH and the Metropolitan Police)

Synthetic biology is a new and exciting research field that brings together biological scientists and engineers with the aim of developing new ways to build and alter biological systems and cells. Biological cells can perform a vast array of activities driven by instructions, which are encoded by DNA. This DNA makes up the cells genome, which act as a blueprint for different types of cells and is composed of four complementary chemical building blocks called nucleotides (G, C, A and T) linked together in a sequence. The beauty of DNA is that these building blocks pair up specifically (G-C and A-T) thus the DNA template can be easily copied and replicated. The instructions encoded in DNA are translated specifically into an array of large molecules called proteins which act as the engines of the cell performing all the necessary functions for cells to live divide and grow e.g. the conversion of food sources like sugar into energy. Over the last 20 years advances in our ability to 'read' DNA has resulted in the complete genome sequences of a variety of living organisms including humans. These sequences encode the basic instruction parts for that specific organism. More recent advances in the chemical synthesis of DNA, has resulted in our increasing ability to 'write' DNA. Synthetic biology therefore aims to provide an engineering framework that allows researchers to design and write DNA tailored to specific applications such that these new synthetic DNA sequences can be placed in cells to perform specific human defined functions. One overarching aim at present is to develop a series of foundational techniques in synthetic biology such as assembling complex DNA components, characterising the instruction parts in detail and computer modelling of more complex DNA designs such that these can be applied to different applications. One overarching concept for synthetic biology is the development of standard DNA components that can used in an engineering 'design, build and test' cycle to create new biological systems and cells that display defined and predictable functions. Many researchers, policy makes and national governments anticipate that synthetic biology will provide a range of benefits to society in different industrial sectors including human health; agriculture and food production; environmental protection and remediation; bioenergy and chemical. To accelerate the translation of synthetic biology technology to new applications we propose to establish a national UK Innovation and Knowledge Centre in synthetic biology with three main objectives: (1) To act as an industrial translation engine which translates university and industry based research in synthetic biology into industrial process and products (2) To be an effective vehicle for the support of small to medium sized UK companies including Start-ups in synthetic biology (3) To actively engage in open dialogue with the public and other stakeholders focusing on the risks and benefits of synthetic biology technologies The IKC aims to place the UK as one of the World's leaders in translating academic synthetic biology research into new products and process but under the framework of 'Responsible Innovation' where the public worth and potential risks of specific applications are considered before such applications are implemented or even reach the market. Such an approach will establish new sustainable synthetic biology industries in the UK, allow other non-UK companies to invest in the UK and develop a skilled workforce in synthetic biology all of which will ultimately lead to new economic growth.

In redeveloping the EngD VEIV centre, we will be focussing on three themes in the area: - Vision & Imaging, covering the areas of computer-based interpretation of images. For example, object tracking in real-time video, or face detection and surface appearance capture. UCL now has a broad expertise in medical imaging (see description of CMIC), and also in tracking and interpretation of images (e.g. expertise of Julier and Prince who are on the management team). Previously we have supported several EngD projects in this area: e.g. Philips (structure from MRI), Sortex (object detection), Bodymetrics (body measurement from scanning data), where the innovation has been in higher-levels of interpretation of imaging data and derivation of measurements automatically. Two other projects highlight the rapidly developing imaging technology, with high-density sensors and high dynamic range imagery (e.g. BBC and Framestore). We have outline support from several companies for continuing in this area. - Media & Interfaces, covering real-time graphics and interactive interfaces. For example, the use of spatially immersive interfaces, or computer games technology. We have a growing relationship with a number of key games companies (EA, Sony, Eidos, Rebellion), where their concern or interest lies in the management of large sets of assets for complex games software. There is interest in tools for developing imagery (r.g. Arthropics, Geomerics). We also have interest in the online 3D social spaces from IBM and BT. A relatively recent development that we plan to exploit is the combination of real-time tracking, real-time graphics and ubiquitous sensing to create augmented reality systems. Interest has been expressed in this area from Selex and BAe. There is also a growing use of these technologies in the digital heritage area, which we have expertise in and want to expand. - Visualisation & Design, covering the generation and visualisation of computer models in support of decision-making processes. For example, the use of visualisation of geographic models, or generative modelling for architectural design. Great advances have been made in this area recently, with the popularity of online GIS tools such as Google Earth tied in to web services and the acceptance of the role of IT in complex design processes. We would highlight the areas of parameterised geometry (e.g. with Fosters and the ComplexMatters spin-out), studying pedestrian movements (with Buro Happold, Node Architects), visualisation of GIS data (e.g. ThinkLondon, Arup Geotechnical), and medical visualisation.These themes will be supported by broadening the engagement with other centres around UCL, including: the UCL Interaction Centre, the Centre for Medical Image Computing, the Chorley Institute and the Centre for Computational Science.The main value of the centre is that visual engineering requires cross-disciplinary training. This is possible with a normal PhD, but within the centre model inter-disciplinary training can embed the students' focussed research into a larger context. The centre model provides a programme structure and forums to ensure that opportunities and mechanisms for cross-disciplinary working are available. The centre also provides an essential role in providing some core training; though by its nature the programme must incorporate modules of teaching from a wide variety of departments that would otherwise be difficult to justify.

We propose to create the EPSRC Centre for Doctoral Training (CDT) in intelligent integrated imaging in healthcare (i4health) at University College London (UCL). Our aim is to nurture the UK's future leaders in next-generation medical imaging research, development and enterprise, equipping them to produce future disruptive healthcare innovations either focused on or including imaging. Building on the success of our current CDT in Medical Imaging, the new CDT will focus on an exciting new vision: to unlock the full potential of medical imaging by harnessing new associated transformative technologies enabling us to consider medical imaging as a component within integrated healthcare systems. We retain a focus on medical imaging technology - from basic imaging technologies (devices and hardware, imaging physics, acquisition and reconstruction), through image computing (image analysis and computational modeling), to integrated image-based systems (diagnostic and interventional systems) - topics we have developed world-leading capability and expertise on over the last decade. Beyond this, the new initiative in i4health is to capitalise on UCL's unique combination of strengths in four complementary areas: 1) machine learning and AI; 2) data science and health informatics; 3) robotics and sensing; 4) human-computer interaction (HCI). Furthermore, we frame this research training and development in a range of clinical areas including areas in which UCL is internationally leading, as well as areas where we have up-and-coming capability that the i4health CDT can help bring to fruition: cancer imaging, cardiovascular imaging, imaging infection and inflammation, neuroimaging, ophthalmology imaging, pediatric and perinatal imaging. This unique combination of engineering and clinical skills and context will provide trainees with the essential capabilities for realizing future image-based technologies. That will rely on joint modelling of imaging and non-imaging data to integrate diverse sources of information, understanding of hardware the produces or uses images, consideration of user interaction with image-based information, and a deep understanding of clinical and biomedical aims and requirements, as well as an ability to consider research and development from the perspective of responsible innovation. Building on our proven track record, we will attract the very best aspiring young minds, equipping them with essential training in imaging and computational sciences as well as clinical context and entrepreneurship. We will provide a world-class research environment and mentorship producing a critical mass of future scientists and engineers poised to develop and translate cutting-edge engineering solutions to the most pressing healthcare challenges.