Institute for the
Future of Computing
The Institute for the Future of Computing was established at the Oxford Martin School in 2010 and the grant from the School ended in 2014. The Institute's Directors were Professor David de Roure and Professor Bill Roscoe.
We address the challenges brought about by the ubiquity and accelerating speed of computers, the massive increase of digital data, complexity of extreme computing and requirements for usable secure systems.
The future is a data driven society. New computing technologies will help develop advanced algorithms for climate modelling, simulations to support research into disease, and analytical capacity for mapping vast quantities of complex information.
We help accelerate research through the development of innovative computational and information technology in multidisciplinary collaborations. Our initiatives include developing energy efficient algorithms; novel methodologies for design, engineering and analysis of reliable wireless sensor networks; technologies for reasoning across large-scale data; and secure mechanisms for computer networking and data transfer.
Enhancing wireless communication in challenging environments: investigates the use of magneto-induction to overcome the problems of traditional radio-based sensor networks, to allow wireless sensor networks to function in even the most challenging of environments, such as undergroud or in water.
Body Sensor Network Security using Human Interactive Channels: we are working to build a dynamic binding protocol and eXtensible Resource Identifier (XRI) based ID scheme in order to better protect body sensor networks against leaks of sensitive personal information and other attacks. We aim to show how a human interactive channel can be used for wireless sensor network security protection.
Automated analysis of web documents: IVLIA: a semantic and context-aware search and annotation engine with data-extraction capabilities, which uses domain-knowledge and context models to analyse and annotate web documents. This will overcome the lack of domain-specific knowledge processing, context-aware filtering and trade precision, which is needed for scalability of web extraction tools.
Energy Efficient and Energy-Aware Algorithms: to address the major concern of high energy consumption in computing systems, we are aiming to create energy efficient or energy-aware algorithms, in order to make energy savings in software, while retaining performance.