| KEYWORD |
Biomimetic Design of Photonic Devices for Neuromorphic Computing
keywords BIOMIMETICS, NEUROMORPHICS, SIMULATION, PHOTONICS
Reference persons ROBERTA BARDINI, STEFANO DI CARLO, ALESSANDRO SAVINO
External reference persons Prof. Peter Bienstman
Dr. Alessio Lugnan
Alessandro Foradori
Tzamn Melendez Carmona
Research Groups DAUIN - GR-24 - reSilient coMputer archItectures and LIfE Sci - SMILIES
Description This thesis explores the biomimetic design of photonic devices, focusing on neuromorphic computing applications. Neuromorphic computing, which seeks to mimic the structure and function of biological neural networks, can greatly benefit from the unique properties of photonic devices. These devices offer high-speed processing, energy efficiency, and parallelism, making them promising for future AI architectures.
Ring resonators, in particular, are suited for neuromorphic computing because they support plasticity-like mechanisms through temperature and free-carrier-based volatile memory and phase-change material (PCM)-based non-volatile memory. These mechanisms closely resemble the intrinsic and synaptic plasticity in biological neurons.
This thesis aims to design photonic architectures for neuromorphic computing by linking specific neuronal plasticity mechanisms with their photonic counterparts. The student will implement biological and photonic models in the NEST simulator, create consistent relationships, and use biological insights to design more adaptive and efficient photonic networks. This biomimetic approach will advance photonic device design for neuromorphic AI systems.
Deadline 10/12/2025
PROPONI LA TUA CANDIDATURA