The simultaneous advances in artificial neural networks and photonic integration
technologies have spurred extensive research in optical computing and optical neural …

Abstract Machine learning (ML) and neuromorphic computing have been enforcing problem-
solving in many applications. Such approaches found fertile ground in optical …

Microcavities enable the generation of highly efficient microcombs, which find applications in
various domains, such as high-precision metrology, sensing, and telecommunications. Such …

Photonic neural networks have significant potential for high-speed neural processing with
low latency and ultralow energy consumption. However, the on-chip implementation of a …

Modern machine-learning applications require huge artificial networks demanding
computational power and memory. Light-based platforms promise ultrafast and energy …

Silicon Photonics, the technology where optical devices are fabricated by the mainstream
microelectronic processing technology, was proposed almost 30 years ago. I joined this …

The recognition of human actions in videos is one of the most active research fields in
computer vision. The canonical approach consists in a more or less complex preprocessing …

Vertical-Cavity Surface-Emitting Lasers (VCSELs) are highly promising devices for the
construction of neuromorphic photonic information processing systems, due to their …

As a resonator-based optical hardware in analog optical computing, a microring synapse
can be straightforwardly configured to simulate the connection weights between neurons …

Task specific hyperparameter tuning in reservoir computing is an open issue, and is of
particular relevance for hardware implemented reservoirs. We investigate the influence of …