Federico Corradi
Assistant Professor in Electrical Engineering, researches neuromorphic computing, from models to microelectronic architectures for efficient deep learning.

Federico Corradi
Dr. Federico Corradi is an Assistant Professor in the Electrical Engineering Department. His research activities are in Neuromorphic Computing and Engineering and span from the development of efficient models of computation to novel microelectronic architectures, with CMOS and emerging technologies, for both efficient deep learning and brain-inspired algorithms. His long-term research goal is to understand the principles of computation in natural neural systems and apply those for the development of a new generation of energy-efficient sensing and computing technologies. His research outputs find use in several application domains as robotics, machine vision, temporal signal processing, and biomedical signal analysis.
Dr. Corradi received a Ph.D. degree from the University of Zurich in Neuroinformatics and an international Ph.D. from the ETH Neuroscience Centre Zurich in 2015. He was a Postgraduate at the Institute of Neuroinformatics in 2018. From 2015 to 2018, he worked in the Institute of Neuroinformatics’ spin-off company Inilabs, developing event-based cameras and neuromorphic processors. From 2018 to 2022, he was at IMEC, the Netherlands, where he started a group focusing on neuromorphic ICs design activities. His passion for research recently brought him back to academia while keeping strong ties with startups and companies.
He is an active review editor of Frontiers in Neuromorphic Engineering, IEEE, and other international journals. In addition, he currently serves as a technical program committee member of several machine learning and neuromorphic symposiums and conferences (ICTOPEN, ICONS, DSD, EUROMICRO).
Contributions
Workshops
- Low-power Spiking Neural Network Processing Systems for Extreme-Edge Applications
June 8, 2023 at 18:00 - 19:30 CET
Join Dr. Federico Corradi as he explores low-power spiking neural network processing systems, offering insights into energy-efficient computing for extreme-edge applications.