Irene Fagnani

About me

I started a PhD in Neuromorphic Computing in February 2026, under the supervision of Professor Fredrik Sandin. I’m interested in bio- and brain-inspired algorithms and how they can be implemented on new and emerging hardware, especially for energy-efficient, real-world applications.

I work on simulating and training neural networks for photonic hardware. The aim is to reduce the gap between the physics of devices and their algorithmic implementation (device mismatch), making models adaptable to different hardware characteristics and aging effects, and taking advantage of the speed of light to achieve fast computation.

 I received both my Bachelor’s degree (October 2023) and Master’s degree (December 2025, major: Statistical Learning) in Mathematical Engineering from Politecnico di Milano. During my studies, I spent Autumn 2024 as an Erasmus student at LUT University in Lappeenranta, Finland.

I carried out my Master’s thesis at Ericsson Research in Stockholm in Spring 2025, where I worked on Spiking Neural Networks for Digital Predistortion in Radio Frequency Power Amplifiers

Other profiles: GitHub , Google Scholar