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- Lecturer
- Dept of Electronic & Electrical Eng
- Faculty of Engineering Science
Dr Adnan Mehonic, Lecturer (Assistant Professor) in Nanoelectronics at UCL and Royal Academy of Engineering Research Fellow
He demonstrated 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, 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 Front. in Materials and a special issue for Front. 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. He is the inventor of more than 10 resistance-switching patents and co-founder 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. He has been named to MIT Technology Review’s annual list of Innovators under 35 in 2021.
Education:
He received a BSc in Electronic Engineering in 2009 from the University of Sarajevo 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),




I am currently working on the development of energy-efficient computing systems (neuromorphic systems) based on memristors. I am interested in non-von Neumann computing paradigms where the physics of memristive devices is harnessed to perform both memory and computing in the same medium without the need to transfer data between memory and processing units.
My work includes co-design of devices, circuits and algorithms that would enable on-chip implementation of machine learning/artificial intelligence. I am looking for ways to increase on-device processing by developing application-specific systems with the holistic approach (materials->devices->circuits->algorithms->applications) and considering non-conventional methods for information processing (e.g. spike-based computing).
01-JUN-2020 | Director, MSc in Nanotechnology | Department of Electronic and Electrical Engineering | UCL, United Kingdom |
01-JUN-2019 | Lecturer in Nanoelectronics | Department of Electronic and Electrical Engineering | UCL, United Kingdom |
01-SEP-2017 – 31-AUG-2022 | Royal Academy of Engineering Research Fellow | Department of Electronic & Electrical Engineerin | UCL, United Kingdom |
06-JUN-2013 – 01-SEP-2017 | Research Associate | Department of Electronic & Electrical Engineerin | UCL, United Kingdom |
2014 | Doctorat | University College London | |
2010 | Master of Science | University College London |