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Online Seminar | Memristors - from memory to the future of brain-inspired computing
09 December 2020, 11:30 am–12:30 pm
Adnan Mehonic, Royal Academy of Engineering Research Fellow and member of the Institute of Communications and Connected Systems will present case studies and showcase the potential of memristors for future technologies.
This event is free.
Event Information
Open to
- All | UCL staff | UCL students
Availability
- Yes
Cost
- Free
Organiser
-
Robert Thompson – Institute of Communications and Connected Systems
Memristors - from the future of memory to bio-inspired computing
An exponential increase in demand for computing power and the slowdown of Moore's law makes a strong case for the exploration of alternative technologies.
Although the memristor technology is currently still in development, it is a strong candidate for future non-volatile memory technology and the non-CMOS and beyond von-Neumann computing solutions.
Since its early development in 2008, memristor technology expanded remarkably to include many different materials systems, physical mechanisms, and novel memory and computing approaches. Small memory chips based on memristors are already being sold by several companies, while large industrial projects demonstrated high-performance memristive computing systems.
Here, I will present and discuss a few representative case studies and showcase the potential role of memristors for the future of memory technologies and the expanding field of AI hardware and brain-inspired computing.
ICCS Chair
This session will be chaired by: Izzat Darwazeh
Attending the seminar
The Seminar will be held on the Zoom platform. Details of how to access Zoom can be found on their website.
Please click this URL to join. Zoom Webinar
Webinar ID: 944 8023 5219
Password: Will be distributed to ICCS members, others are welcome to join and the password can be requested by email.
About the Speaker
Adnan Mehonic
Lecturer in Nanoelectronics and Royal Academy of Engineering Research Fellow at UCL
Dr Mehonic received a BSc in Electronic Engineering from the University of Sarajevo in 2009 and was awarded the Golden Badge, the best student award. He graduated from University College London (UCL) with an MSc in Nanotechnology (Distinction, Oxford Instruments prize for the best MSc project) in 2010 and PhD in 2014 (top 3 best PhD thesis in 2013/14, EE Department), demonstrating the first ambient operating all-SiOx memristor. He has been working as a Research Associate in the group of Electronic Materials and Devices, EEE UCL till 2017, further developing silicon oxide memristive technology. In 2017, he was awarded a highly prestigious 5-year Royal Academy of Engineering Research Fellowship to work on neuromorphic technology for energy-efficient AI hardware. In 2019, he was appointed as a Lecturer in Nanoelectronics. He serves on the advisory boards of Wiley’s Adv. Intelligent Systems and is an Editor for Frontiers in Materials and Frontiers in Nanotechnology. He is a board member for IoP’s Dielectrics and Electrostatics group, and an IoP and IET member. At the EEE department, he is the director of the MSc in Nanotechnology.
To date, he has authored more than 40 journal publications and over 60 international conference proceedings (including more than ten invited talks). His research resulted in two major EPSRC project grants - EP/K01739X/1 in 2013 and EP/P013503/1 in 2016, and a Leverhulme grant in 2016 , and the RAEng Research Fellowship in 2017. He is the inventor of 5 resistance-switching patents and co-funder of spinout company (“IntrinSic Semiconductor Technology”), where he serves as a Chief Technology Officer. He received the “One to Watch 2015” award from UCL Enterprise for UCL’s most innovative staff.
His current work is focused on energy-efficient nanoelectronics and functional materials. More specifically, he works on non-von Neumann computing paradigms harnessing the physics of memristive devices to perform both memory and computing. He is interested in circuits and algorithms for on-chip implementation of ML/AI and nonconventional information processing algorithms (e.g. spike-based computing).
More about Adnan Mehonic