This PhD project explores the development of ultrafast, energy-efficient neuromorphic sensing systems using quantum tunnelling-based optoelectronic devices. Inspired by the brain’s ability to process events rapidly, the research focuses on photonic–electronic platforms that mimic neural spiking behavior for in-sensor processing.

Key technologies include resonant tunnelling diodes (RTDs) and vertical-cavity surface-emitting lasers (VCSELs), engineered to exhibit controllable quantum tunnelling effects at room temperature. These devices act as artificial spiking neurons, converting optical and electrical stimuli into high-speed spike-encoded signals.

The project will:

• Design and fabricate neuromorphic devices operating at telecom wavelengths (850, 1310, 1550 nm) for compatibility with existing fibre-optic networks.
• Integrate these devices with fibre-optic sensing platforms (e.g., Fibre Bragg Gratings and Distributed Acoustic Sensors) to detect and classify events like strain, temperature, turbulence, and RF/audio signals.
• Enable ultrafast optical communication of event signals via fibre or wireless links for applications in infrastructure monitoring, fault detection, and security.
• Collaborate with Fraunhofer UK to explore real-world applications in energy, security, and manufacturing.
• Develop neuromorphic algorithms to support spike-based sensing and processing.

This interdisciplinary research combines photonics, quantum tunnelling, neuromorphic computing, and sensing technologies to create next-generation smart sensing systems for edge computing and remote monitoring.