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Workshop on Neuromorphic Organic Devices

Istituto Italiano Di Tecnologia

Workshop on Neuromorphic Organic Devices

The 1st Workshop on Neuromorphic Organic Devices will be held at Istituto Italiano di Tecnologia (IIT)-Center for Translational Neurophysiology (CTNSc) in Ferrara, Italy from 12-14 June 2019.   (See Program !)

Neuromorphic devices couple together information and computation functions. When interrogated in a dynamic mode, these devices elicit a response whose features can be assimilated to those of biological synapses. It is then possible to “train” them to learn, to consolidate their memory constant, and to integrate them into artificial neural networks, thus forming the basis for logic paradigms alternative to binary logic.

Since the demonstration of NOMFET synapses in 2010, organic electronics devices, based on either organic semiconductors or hybrid organic/inorganic nanomaterials, were demonstrated to be suitable for operations as neuromorphic devices. There has been an increasing activity and interest from the organic electronics, and especially organic bioelectronics, communities towards neuromorphic electronics, understanding the fundamental mechanisms giving rise to the response, designing new materials for these properties, and envision new applications for neuromorphic device architectures.

The “1st Workshop on Neuromorphic Organic Devices” gathers scientists and engineers from different fields and disciplines with the aim to discuss together in an open and informal environment the current trends of neuromorphic organic devices, also trying to identify future directions and foster international collaborations.

Relevant topics (the list is not exclusive):
· neuromorphic logic and artificial neural networks;
· solid-state and hybrid synapstors;
· synapstors operated in electrolytes;
· modelling and simulations;
· materials design for neuromorphic neural networks;
· sensors and biosensors;
· neuromorphic device architectures for the Central Nervous System;
· neural implants and prosthetics;
· brain-machine interfaces;
· applications to neurosciences.