The ever-increasing demand for artificial intelligence (AI) systems is underlining a significant
requirement for new, AI-optimised hardware. Neuromorphic (brain-like) processors are one …

In this work, we introduce an interconnected nano-optoelectronic spiking artificial neuron
emitter-receiver system capable of operating at ultrafast rates (about 100 ps/optical spike) …

Neuromorphic photonic computing has emerged as a competitive computing paradigm to
overcome the bottlenecks of the von-Neumann architecture. Linear weighting and nonlinear …

We propose an inferencing framework of a hybrid-integrated photonic spiking neural
network (PSNN) to perform pattern recognition tasks, where the linear computation is …

Big data processing and large-scale computational needs will soon be limited by local on-
chip power dissipation of available semiconductor technologies. Moreover, the increasing …

Optoelectronic artificial spiking neurons are regarded as promising core elements for novel
photonic neuromorphic computing hardware. In this work, we investigate a modular …

Photonic convolutional neural networks (PCNNs) are gaining attention owing to their
potential to overcome the von Neumann bottleneck. Here, we propose and demonstrate …

Interconnectivity between functional building blocks (such as neurons and synapses)
represents a fundamental functionality for realizing neuromorphic systems. However, in the …

We report experimentally on high-speed, tuneable photonic synaptic architectures realized
with vertical cavity surface emitting lasers (VCSELs) connected in series and in parallel …

Pavlovian associative learning, a form of classical conditioning, has significantly impacted
the development of psychology and neuroscience. However, the realization of a prototypical …