About the Seminar

Artificial Intelligence (A.I.) is destined to transform our society, affecting every aspect of our lives. However, a key bottleneck towards the proliferation of the technology is the lack of efficient hardware that will allow us to embed A.I. everywhere– well beyond the cloud’s reach. Up until now, the processing of data in electronics has relied on assemblies of vast numbers of transistors – microscopic switches that control the flow of electrical current by turning it on or off. Transistors have got smaller and smaller in order to meet the increasing demands of technology, but have nowadays reached their physical limit, with – for example – the processing chips that power smartphones containing an average of seven billion transistors that are only a few atoms wide.

A novel nanoelectronic technology, known as the memristor, proclaims to hold the key to a new era in electronics and A.I., being both smaller and simpler in form than transistors, low-energy, and with the ability to retain data by ‘remembering’ the amount of charge that has passed through them – akin to the behaviour of synaptic connections in the human brain. In his lecture, Themis Prodromakis will present a few examples on how such technologies can be used in practical applications, demonstrating our ability to deliver “A.I. on a chip”.

About the Speaker

Professor Themis Prodromakis received his BEng. (2003) from University of Lincoln, MSc. (2004) from University of Liverpool and Ph.D. (2008) from Imperial College London. He previously held a Corrigan Fellowship in Nanoscale Technology and Science, funded by the Corrigan Foundation and LSI Inc., within Imperial College and a Lindemann Trust Visiting Fellowship in EECS UC Berkeley. Since 2013, he has been with the University of Southampton, where he is currently Professor in Nanotechnology and Royal Society Industry Fellow and leads the Electronic Materials & Devices Group within the Zepler Institute. He is Fellow of the IET and the Institute of Physics and serves as Director for the Lloyd's Register Foundation International Consortium for Nanotechnology (ICoN: www.lrf-icon.com) and UKRI Centre for Doctoral Training in Machine Intelligence for Nano-Electronic Devices and Systems (MINDS).