Neuromorphic technologies

We are driving advancements in neuromorphic engineering, a field that emulates the structure and functionality of the human brain to revolutionise computing.

Within the department, groundbreaking work includes the development of technologies like memristor-based memory, which emulates the structure and function of neural networks. These advances significantly improve power efficiency and data processing speeds, paving the way for future devices that are faster, smarter, and more cost-effective.

Our efforts in neuromorphic engineering aim to transform computational paradigms, enabling revolutionary progress in fields such as robotics, AI, and real-time data analysis. This research holds the potential to drive efficiency and functionality in next-generation technologies, positioning the department at the forefront of this rapidly evolving discipline.

Explore related news, projects and case studies below.

News

Prof Kenyon speaks to Nature Reviews Electrical Engineering about the UK’s neuromorphic ecosystem

Prof Tony Kenyon, Director of the Neuroware IKC, told Nature Reviews Electrical Engineering about its vision for brain-inspired technologies.

04 Nov 2025

UCL to lead UK’s first brain-inspired computing centre

UCL will lead Neuroware, the UK’s first centre for brain-inspired computing, driving energy-efficient technologies from the lab into real-world use.

19 Sep 2025

Dr Adnan Mehonic awarded prestigious EU-40 Materials Prize

Dr Adnan Mehonic has received the EU-40 Materials Prize from E-MRS, recognising his impactful research in nanoelectronics and materials science.

22 Aug 2025

Research projects

Inter-connect quantum compute resources via qubit communications utilising entanglement

Exploring optical network systems to enable distributed quantum computing through qubit communication and entanglement.

15 Jan 2025

NeuMat Network: Neuromorphic Materials and Devices for Innovative AI hardware

This project unites UK academia and industry to create a national community advancing next-generation neuromorphic materials and energy-efficient AI hardware.

15 Jan 2025

The future of memristive technologies