Current Position:
Professor of Nanotechnology; Director, Centre for Electronics Frontiers
Institution:
University of Southampton
Discipline:
Materials Science & Nanotechnology
Recognized for: Developing a new nanoscale electronic component, known as a “memristor” and electronic circuits based on memristor technology that surpass conventional computer circuits in artificial intelligence (AI) computations. His research, along with his entrepreneurship efforts, has brought the memristor technology one step closer to becoming viable in the electronics industry.
Areas of Research Interest and Expertise: Memristor, Nano-electronics, Artificial Intelligence Hardware, Neural Networks, Bioelectronics
Previous Positions:
BSc, University of Lincoln, UK
MSc, University of Liverpool, UK
PhD, Imperial College London, UK
Research Fellow, Imperial College London, UK
Research Fellow, University of California, Berkeley, USA
Research Summary:
Artificial Intelligence (AI) is transforming our society. However, a key bottleneck towards its widespread use is the lack of efficient hardware. Themis Prodromakis, PhD, has made remarkable contributions in devising new hardware that supports the increasing computational demands of the AI era. His technology is built upon an electronic component known as a “memristor”, or memory-resistor, which has the ability to 'remember' the amount of charge that has passed through it, thereby simultaneously storing multiple units of data in a single component.
Prodromakis has developed some of the first memristor technologies that are promising for real applications. He first used nanoscale materials to fabricate stable, reliable, and low-energy consumption memristors. He then used those memristors to build novel artificial neural networks—computer circuits emulating the structure of the human brain—that support state-of-the-art machine learning and high speed big-data processing. He further introduced a new circuit design paradigm by embedding memristors within conventional computer circuits, significantly boosting their performance while maintaining a low energy consumption. He has also invented memristor bio-sensors that monitor large-scale neural signals in real time and chips that can communicate with brain neurons over the internet. Several technologies and testing tools he developed have been successfully commercialized and utilized by global businesses and standards organizations. Taken together, he has pushed memristor technologies to become a viable solution to the challenges we face today in the information and biomedical industries.
"The invention of the transistor and integrated circuits have over the past 7 decades transformed our world. Sustaining modern societal needs requires a fundamental re-think of electronics and Memristors promise to bring this change about. I am truly honoured that the contributions of my team and collaborators are recognized with this prestigious award."
Key Publications:
A. Serb, A. Corna, R. George, et al., T. Prodromakis. Memristive Synapses Connect Brain and Silicon Spiking Neurons. Scientific Reports, 2020.
A. Serb, A. Khiat, T. Prodromakis. Seamlessly Fused Digital-analogue Reconfigurable Computing Using Memristors. Nature Communications, 2018.
I. Gupta, A. Serb, A. Khiat, R. Zeitler, S. Vassanelli, T. Prodromakis. Real-time Encoding and Compression of Neuronal Spikes by Metal-oxide Memristors. Nature Communications, 2016.
A. Serb, J. Bill, A. Khiat, R. Berdan, R. Legenstein, T. Prodromakis. Unsupervised Learning in Pobabilistic Neural Networks with Multi-state Metal-oxide Memristive Synapses. Nature Communications, 2016.
Other Honors:
| 2019 | Chair in Emerging Technology – AI Hardware, Royal Academy of Engineering |
| 2018 | University Research Group of the Year Finalist, TechWorks Awards |
| 2018 | University Research Award Finalist, Elektra Awards |
| 2017 | Industry Fellowship, Royal Society |
| 2017 | 100A1 Ambassador, Lloyd’s Register Foundation |
| 2013 | Early Career Fellowship, Engineering and Physical Sciences Research Council |
In the Media:
Futurism – Artificial and Biological Neurons Just Talked over The Internet
Science Daily – New study allows brain and artificial neurons to link up over the web
Labiotech.eu –Scientists Connect Brain Cells to Machines Over the Internet
Electronics Weekly –Southampton breaks memristor record with 7bits/cell
Science Daily –New technology standard could shape the future of electronics design
Electronics Weekly –Memristors key to nano-scale analogue/digital adaptive hardware
IEEE Spectrum –Memristors Could Be a Boon to Brain-to-Prosthesis Communication
Engineering.com –Watch Out, Transistors: Memristors Gaining Traction
Electronics Weekly –Southampton builds memristor neural learning network
Phys.org –'Missing link' found in the development of bioelectronic medicines