Stephen B. Furber

Stephen B. Furber is the ICL Professor of Computer Engineering in the Department of Computer Science at the University of Manchester, UK. He previously served as Head of Department from 2001 to 2004.

His educational background includes a PhD in aerodynamics from the University of Cambridge (1974-1980), followed by a Rolls-Royce Research Fellowship at Emmanuel College, Cambridge (1978-1981). Prior to his academic career, he worked at Acorn Computer Ltd in Cambridge from 1981 to 1990, where he progressed from hardware designer to head of Advanced R&D.

Professor Furber's research focuses on computer engineering with specialization in low-power system design, asynchronous digital systems, systems-on-chip, networks-on-chip, and neural systems engineering. His work is primarily associated with the Advanced Processor Technologies (APT) group at Manchester, which conducts cutting-edge research in many-core systems and neuromorphic computing, including the development of the million-core SpiNNaker brain-modelling machine.

His research has significant implications for energy-efficient computing, brain science, and improving the energy efficiency of machine learning and AI applications. The APT group's work addresses challenges posed by the impending end of Moore's Law through advanced architectural techniques.

• CBE (Commander of the Order of the British Empire), for services to computer science (2008)
• Member of Academia Europaea (2008)
• IET Faraday Medal (2007)
• Fellow of the IEEE (2005)
• Royal Society-Wolfson Research Merit Award (2004-2009)
• Royal Academy of Engineering Silver Medal (2003)
• Fellow of the Royal Society, UK (2002)
• Fellow of the Royal Academy of Engineering, UK (1999)

Professor Furber leads research that bridges hardware design and neural systems engineering. His work on the SpiNNaker platform represents one of the world's largest neuromorphic computing systems, supporting an open service under the European Human Brain Project with global users. He actively collaborates with industry leaders to address challenges in energy-efficient computing at scale.

The Advanced Processor Technologies group he is affiliated with conducts research across multiple domains including many-core systems, neuromorphic computing, and parallel and distributed computing. The group welcomes postgraduate students interested in MPhil or PhD studies and seeks collaborations with companies and academic groups.