Imperial College London

Professor Themis Prodromakis

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Honorary Research Fellow



+44 (0)20 7594 0840t.prodromakis Website




B422Bessemer BuildingSouth Kensington Campus





Themis holds the Regius Chair of Engineering at the University of Edinburgh and Director of the Centre for Electronics Frontiers. His work focuses on developing metal-oxide Resistive Random-Access Memory technologies and related applications and is leading an interdisciplinary team comprising 30 researchers with expertise ranging from materials process development to electron devices and circuits and systems for embedded applications. He holds a Royal Academy of Engineering Chair in Emerging Technologies and a Royal Society Industry Fellowship. He is an Adjunct Professor at UTS Australia, visiting Professor at the Department of Microelectronics and Nanoelectronics at Tsinghua University, and Honorary Fellow at Imperial College London. He is Fellow of the Royal Society of Chemistry, the British Computer Society, the IETand the Institute of Physics and is also Senior Member of the IEEE. He has served as the Director of the Lloyds Register Foundation International Consortium for Nanotechnology (ICoN) and Co-Director of the UKRI Centre for Doctoral Training in Machine Intelligence for Nanoelectronic Devices and Systems (MINDS). In 2015, he established ArC Instruments Ltd that delivers high-performance testing infrastructure for automating characterisation of novel nanodevices in over 16 countries and in 2019 he founded that is building new power-efficient hardware solutions.



Tzouvadaki I, Gkoupidenis P, Vassanelli S, et al., 2023, Interfacing Biology and Electronics with Memristive Materials., Adv Mater, Vol:35

Panca A, Panidi J, Faber H, et al., 2023, Flexible Oxide Thin Film Transistors, Memristors, and Their Integration, Advanced Functional Materials, Vol:33, ISSN:1616-301X

Huang J, Serb A, Stathopoulos S, et al., 2023, Text classification in memristor-based spiking neural networks, Neuromorphic Computing and Engineering, Vol:3

Tzouvadaki I, Prodromakis T, 2023, Large-scale nano-biosensing technologies, Frontiers in Nanotechnology, Vol:5


Prodromakis T, Papavassiliou C, Si Z, et al., An improved data-driven memristor model accounting for sequences stimulus features, 2023 IEEE International Symposium on Circuits and Systems (ISCAS), IEEE, ISSN:2158-1525

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