Davide Rossetti

Ph.D. candidate in Ingegneria Elettrica, Elettronica E Delle Comunicazioni , 39th cycle (2023-2026)
Department of Electronics and Telecommunications (DET)



Research topic

Reservoir Computing: Theory, Implementation and Algorithms


Research interests

Big Data, Machine Learning, Neural Networks and Data Science
Biomedical devices and applications
Electronic devices: modeling and characterization
Micro- and nanotechnologies, devices, systems and applications


Davide Rossetti is a Physical Engineer. He obtained a double degree in Physics of Complex Systems at the Politecnico di Torino and at the Université Paris Saclay in 2023 with highest honours, summa cum laude. During his master's thesis, he completed an internship at the LISN labs of Paris Saclay, where he focused on modelling causality in stochastic nonlinear systems through machine learning.

Davide is currently pursuing a PhD at the Politecnico di Torino, where he is working on the exploration of Reservoir Computing and Memristive Technologies. The research focuses on energy-efficient edge computing through the development of theoretical foundations and hardware prototypes for Reservoir Computing (RC). By using a delay-free single-node empowered by memristive devices, the approach enables in-memory vector matrix multiplication (VMM) in a single step. RC, a low-power neuromorphic paradigm, proves ideal for intelligent edge computing by extending temporal information to a trainable readout layer through a nonlinear dynamic system. The research uses memristor technology for both reservoir and readout, which enables theory-driven hardware optimisation. The goal of his project is to provide a theoretical foundation, hardware implementation and benchmark for an efficient and scalable RC platform, contributing to the development of green AI in edge computing devices.

As part of his academic and professional commitments, he is a member of the IEEE HKN Society, showcasing his commitment to excellence and leadership in the field of electrical and computer engineering.