XMOS Ltd

Multi-touch tables, such as Microsoft Surface, are now widely available. Users can walk-up and use these systems in hotel lobbies and other public settings with very little instruction and with no need to wear or hold intrusive sensors with their hands or body. The ability to 'walk-up and use' with unadorned hands and fingers removes the barrier between human and technology, encouraging spontaneous use. One of the primary disadvantages of current interactive surfaces is that users can touch objects, but they are unable to feel them. There are a plethora of applications where it is beneficial for the user to have their touches augmented with 'feel-based' haptic feedback. For example, medical applications, virtual training, and modelling applications require precise control from the user-haptic feedback can aid the user in effectively performing these tasks. These applications demonstrate the benefit of augmenting haptic feedback with visual feedback in an interactive application. Often, the visual space has been disconnected from the force-feedback, requiring a prolonged training period for the user to become accustomed to moving a digital object and watching the interactions a small distance away on a monitor. In this proposal we will investigate the use of ultrasound transducers to provide 'feelable' feedback through air. The skin on a human hand can feel the ultrasonic pressure wave produced by a carefully calibrated series of transducers, in much the same manner that is apparent from loud sub-woofers on a stereo system. Ultrasound waves are outside the human's range of hearing and so provide silent, through-air haptic feedback. We will use this technology to provide multi-point haptic feedback on the surface of a multi-touch horizontal surface. The team consists of Dr. Sriram Subramanian, Dr. Mark Marshall and Dr. Jason Alexander from the computer science departments and Prof. Bruce Drinkwater from the Mechanical Engineering department of the University of Bristol and Prof. Stephen Brewster from the Computer Science department of the University of Glasgow. The team is internationally recognised for its research in Human-Computer Interaction (HCI), novel integration of hardware for HCI, and Ultrasonic sensors. Microsoft research (Cambridge) and XMOS will serve as project partners and offer valuable resources and support for the project.

Advances in cryptanalysis are often produced by mathematicians who seek techniques to unravel the hard problems on which modern cryptosystems are based. Attacks based on the concept of physical security move the art of cryptanalysis from the mathematical domain into the practical domain of implementation. By considering the implementation of cryptosystems rather than purely their specification, researchers have found they can mount physical attacks which are of low cost, in terms of time and equipment, and are highly successful in extracting useful results. Recent examples that demonstrate the real-world impact of such attacks are those against the KeeLoq range of RFID devices used for car and building access control, and MIFARE contactless smart-cards (e.g. the ``Oyster'' cards used by the London Underground).Side-channel attacks are a genre of physical attack based on the assumption that one can passively observe an algorithm being executed by some hardware device, and infer details about the internal state of computation from the features that occur. A typical side-channel attack consists of a collection phase that provides the attacker with profiles of execution, and an analysis phase which recovers otherwise secret information from the profiles. Focusing on power and EM based attacks in particular, countermeasures against side-channel attack are increasingly well understood on a case by case basis; at a high-level they can be classified as either hiding (breaking the link between execution and profiles) or masking (breaking the link between execution and algorithm). Approaches to hiding style countermeasures typically attempt to make each profile constant for all secrets, or entirely random; in both cases the premise is that a profile can no longer be correlated to the secret information.There are a number of approaches to implementing these sorts of countermeasure. At the highest-level, one can consider alternate algorithms (or implementation approaches) that realise hiding or masking in software. On one hand this approach is very algorithm-specific and can imply a significant performance penalty; on the other hand, no alterations are required to the hardware on which the software executes. At the lowest-level, one can consider using so-called secure logic styles; the basic idea is to replace CMOS cell libraries with alternatives which, for example, consume a constant amount of power regardless of the result they compute. The major disadvantage of this approach is the resulting overhead in terms of area; the major advantage is that the approach is largely algorithm-agnostic, i.e. is a general solution which can be automatically applied.The research programme within this proposal aims, in a sense, to adopt an approach between these two extremes. The crux of the research is the alteration of a general purpose processor so that countermeasures against side-channel attack are implemented at the micro-architectural level. The processor will retain the same Instruction Set Architecture (ISA) and hence the same functional characteristics, but the behavioural characteristics will prevent leakage of information via, for example, power analysis. Our focus is on aspects of the micro-architecture which can be randomised in some way. We suggest that this approach will afford a level of flexibility and algorithm agility representing an attractive trade-off between security and other metrics. Specifically, it permits high-level algorithmic countermeasures to be automatically supported by the hardened processor platform (meshing with the ideal of tiered countermeasures rather than a single panacea), while largely avoiding the overhead and sensitivity to underlying process technology traditionally associated with secure logic styles.

Quantum information science and technologies offer a completely new and powerful approach to processing and transmitting information by combining two of the great scientific discoveries of the 20th century - quantum mechanics and information theory. By encoding information in quantum systems, quantum information processing promises huge computation power, while quantum communications is already in its first stages of commercialisation, and offers the ultimate in information security. However, for quantum technologies to have as big an impact on science, technology and society as anticipated, a practical scalable integration platform is required where all the key components can be integrated to a single micro-chip technology, very much akin to the development of the first microelectronic integrated circuits. Of the various approaches to realising quantum technologies, single particles of light (photons) are particularly appealing due to their low-noise properties and ease of manipulation at the single qubit level. It is possible to harness the quantum mechanical properties of single photons, taking advantage of strange quantum properties such as superposition and entanglement to provide new ways to encode, process and transmit information. Quantum photonics promises to be a truly disruptive technology in information processing, communications and sensing, and for deepening our understanding of fundamental quantum physics and quantum information science. However, current approaches are limited to simple optical circuits with low photon numbers, inefficient detectors and no clear routes to scalability. For quantum optic information science to go beyond current limitations, and for quantum applications to have a significant real-world impact, there is a clear and urgent need to develop a fully integrated quantum photonic technology platform to realise large and complex quantum circuits capable of generating, manipulating and detecting large photon-number states. This Fellowship will enable the PI and his research team to develop such a technology platform, based on silicon photonics. Drawing from the advanced fabrication technologies developed for the silicon microelectronics industry, state of the art silicon quantum photonic devices will enable compact, large-scale and complex quantum circuits, experiments and applications. This technology platform will overcome the current 8-photon barrier in a scalable way, enable circuits of unprecedented complexity, and will be used to address important fundamental questions, develop new approaches to quantum communications, enhance the performance of quantum sensing, provide a platform for new routes to quantum simulations, and achieve computational complexities that can challenge the limits of conventional computing. This multidisciplinary research programme will bring together engineers, physicists and industrial partners to tackle these scientific and technological challenges.

The description of the laws of quantum mechanics saw a transformation in society's understanding of the physical world-for the first time we understood the rules that govern the counterintuitive domain of the very small. Rather than being just passive observers now scientists are using these laws to their advantage and quantum phenomena are providing us with methods of improved measurement and communication; furthermore they promise a revolution in the way materials are simulated and computations are performed. Over the last decade significant progress has been made in the application of quantum phenomena to meeting these challenges. This "Engineering Photonic Quantum Technologies" Programme Grant goes significantly beyond previous achievements in the quantum technology field. Through a series of carefully orchestrated work packages that develop the underlying materials, systems engineering, and theory we will develop the knowledge and skills that enable us to create application demonstrators with significant academic and societal benefit. For the first time in quantum technologies we are combining materials and device development and experimental work with the important theoretical considerations of architectures and fault tolerant approaches. Our team of investigators and partners have the requisite expertise in materials, individual components, their integration, and the underpinning theory that dictates the optimal path to achieving the programme goals in the presence of real-world constraints. Through this programme we will adopt the materials systems most capable of providing application specific solutions in each of four technology demonstrations focused on quantum communications, quantum enhanced sensing, the construction of a multiplexed single-photon source and information processing systems that outperform modern classical analogues. To achieve this, our underlying technology packages will demonstrate very low optical-loss waveguides which will be used to create the necessary 'toolbox' of photonic components such as splitters, delays, filters and switches. We will integrate these devices with superconducting and semiconducting single-photon detector systems and heralded single-photon sources to create an integrated source+circuit+detector capability that becomes the basis for our technology demonstrations. We address the challenge of integrating these optical elements (in the necessary low-temperature environment) with the very low latency classical electronic control systems that are required of detection-and-feedforward schemes such as multiplexed photon-sources and cluster-state generation and computation. At all times a thorough analysis of the performance of all these elements informs our work on error modelling and fault tolerant designs; these then inform all aspects of the technology demonstrators from inception, through decisions on the optimal materials choices for a system, to the layout of a circuit on a wafer. With these capabilities we will usher in a disruptive transformation in ICT. We will demonstrate mutli-node quantum key distribution (QKD) networks, high-bit rate QKD systems with repeaters capable of spanning unlimited distances. Our quantum enhanced sensing will surpass the classical shot noise limit and see the demonstration of portable quantum-enhanced spectroscopy system. And our quantum information processors will operate with 10-qubits in a fault tolerant scheme which will provide the roadmap to 1,000 qubit cluster state computing architectures.

Our mission is to train the next generations of innovators in responsible, data-driven and knowledge-intensive human-in-the-loop AI systems. Our innovative, cohort-based training programme will deliver cohorts of highly trained PhD graduates with the skills to design and implement complex interactive AI pipelines solving societally important problems in responsible ways. While fully autonomous artificial intelligence dominates today's headlines in the form of self-driving cars and human-level game play, the key AI challenges of tomorrow are posed by the need for interactive knowledge-intensive systems in which the human plays an essential role, be it as an end-user providing relevant case-specific knowledge or interrogating the system, an operator requiring crucial information to be presented in an intelligible form, a supervisor requiring confirmation that the system's performance remains within acceptable limits, or a regulator assessing to what extent the system operates according to exacting standards concerning transparency, accountability and fairness. Each of these examples demonstrates a need for specific and meaningful interaction between the AI system and human(s). The examples also demonstrate the importance of knowledge for achieving human-level interaction, in addition to the data driving the machine learning aspect of the system. In close conversation with our industry partners we thus identified Interactive Artificial Intelligence (IAI) as a core sub-discipline of AI where the need for and deficit in advanced AI skills is abundantly evident while being homogeneous enough to have intellectual integrity and be taught and researched within the context of a single CDT. The most important aspects of the training programme are: - Knowledge-Driven AI and Data-Driven AI are core components treated in a close symbiotic relationship: the former uses knowledge in processes such as reasoning, argumentation and dialogue, but in such a way that data is treated as a first-class citizen; the latter starts from data but emphasises knowledge-intensive forms of machine learning such as relational learning which take knowledge as an additional input. - Human-AI Interaction is another core component addressing all human-in-the-loop aspects, overseen by a co-investigator from the human-computer interaction field. - Responsible AI is underpinning not just the taught first year but the students' doctoral training throughout all four years, overseen by two dedicated co-investigators with backgrounds in IT law and industrial codes of practice. Other skill requirements from stakeholders include: the ability to design and implement complete end-to-end systems; acquiring depth in some AI-related subjects without sacrificing breadth; the ability to work in teams of people with diverse skill sets; and being able to take on a role as "AI ambassadors" who are able to inspire but also to manage expectations through their in-depth understanding of the strengths and weaknesses of different AI techniques. The IAI training programme is designed to achieve this by strongly emphasising cohort-based training. Students will develop their projects and coursework within an innovative software environment which means easy integration of their work with that of others. This virtual hub is complemented by a physical hub where all cohorts are colocated -- together both hubs will strongly promote interaction both within and between cohorts: e.g., projects can aim at improving or extending software produced by the previous cohort, so that senior students can be involved in mentoring their juniors. In summary, the IAI training programme pulls together Bristol's unique and comprehensive strengths in doctoral training and AI to deliver highly trained AI innovators, equipping them with essential skills to deliver the interactive AI technology society requires to deal with current and future challenges.