Professor Patrick Grant, Pro-Vice-Chancellor (Research) University of Oxford, said: ‘Cloud computing is an essential part of modern research. A streamlined operating model for using cloud services will benefit all of our researchers. The Oxford Robotics Institute, the Cyber Physical Systems Group, and the Human Centred Computing group are leading the initial projects in the short term, but I look forward to growing the collaboration to bring research benefits across our research work more broadly.’
Max Peterson, VP International Sales Worldwide Public Sector, AWS, said: ‘We are excited about this collaboration with the University of Oxford. With AWS, the University will be able to accelerate time-to-science as multiple, large experiments can be conducted in parallel with greater ease and in less time. And by driving cost down, researchers can dramatically increase the scale of computational experimentation. The collaboration demonstrates how academia can use the cloud to deliver excellent science with greater speed, flexibility and security, compared to using on premises data centres. Through our donation we will also support a new generation of researchers accessing cloud-native tools and technology for research through the University’s “Lighthouse” Doctoral Scholarships program.’
Oxford University has a vibrant, large and growing programme in Data Science, AI and Robotics research and development. To support and inspire the research, students, and staff, access to fast-moving, state-of-the-art large-scale computing resources is critical. AWS, one of the leading global cloud providers, offers secure, reliable, scalable, low-cost cloud infrastructure that underpins millions of customers around the world and this collaboration will significantly accelerate the cloud-based research conducted at the University.
Professor Ingmar Posner, Head of Oxford’s Applied AI Lab and founding Director of the Oxford Robotics Institute, said: ‘Reliable and scalable compute infrastructure is a cornerstone of a cutting-edge research agenda in Robotics, Data Science and AI. The bold vision developed jointly by the University and AWS is geared not only towards enabling the sustainable provision of this infrastructure here in Oxford but to provide a blueprint of engagement for others to follow. This generous £7M gift from AWS will enable us to start something truly exceptional - in terms of research here at Oxford but also looking ahead at enabling the broader research landscape.’
Professor Nick Hawes of the Oxford Robotics Institute, coordinator of the activity within the human-machine collaboration initiative, said: ‘This initiative will drive the creation of cloud-first processes for research, including international collaboration, governance, reproducibility, publishing and translation. This first Oxford-AWS strategic collaboration will create eight research projects in topics around autonomy in human contexts across the Departments of Engineering and Computer Science. These will seed the development of a larger AI and robotics ecosystem over the coming years, involving over 50 organisations (universities and companies and public sector stakeholders), and over 60 postdoctoral researchers and PhD students in joint projects.’
Professor Marina Jirotka, Professor of Human-Centred Computing, said: ‘This gift will open up many amazing opportunities. My team is excited to expand our work on the ethical black box for autonomous robots, and lay the foundations for an Institute of Responsible Technology. We look forward to extending the impact of our responsible innovation work into industry.’
Professor Niki Trigoni leads the Cyber Physical Systems group, which focuses on infrastructure-free indoor positioning systems, human robot interaction and autonomous collaboration systems for workplaces ranging from hospitals, to office environments and warehouses. The group has set up an international centre-to-centre collaboration, across the UK, the US and Australia.
Professor Trigoni said: ‘We are focusing on building state of the art situation awareness algorithms for blue light emergency services that combine variety of sensing modalities - inertial, radio, visual, mmWave and thermal. This additional cloud infrastructure will enable efficient, often health/life-critical solutions for human-machine collaborations in the workplace and beyond.’