Stefano Brivio is interested in a research that crosses disciplines as materials science, device physics and computing. Today's possibilities in materials exploration, manipulation, nano-fabrication can be effectively oriented towards the deployment of mixed ionic/electronic/structural/magnetic/... effects to build innovative devices. Novel functionality, their unconventional use and arrangement can be exploited for new computation paradigms. Inspiration from the brains or from the nature, in general, pushes towards systems that respond as a collective entity rather than a sequence of independent logic steps and that are more suitable for the current demands by a society that takes advantage of device interconnection, intelligent gathering of information, automation. As any groundbreaking societal revolution, researcher have the responsibility to take one eye open towards possible ethical risks. all these aspects fall within my research interests.
In concrete terms, my research interests are now directed towards the development of memristive devices with innovative functionalities (dynamical or oscillatory response, fading memory on multi-time scales,...) and towards devising brain-inspired computing systems taking advantage of those.
Non-linear Memristive Synaptic Dynamics for Efficient Unsupervised Learning in Spiking Neural Networks
[adapted with permissions under CCBY license from Brivio et al. Front. Neurosci. 15 (2021)]
Analogue Computing with Dynamic Switching Memristor Oscillators: Theory, Devices and Applications - COSMO
Reference person for CNR-IMM: Stefano Brivio
Memory technologies with multi-scale time constants for neuromorphic architectures - MeM-Scales
Funding: H2020 - ICT
Reference person for CNR-IMM: Sabina Spiga