Low-Power Spiking Neural Network Processing Systems for Extreme-Edge Applications

Join Dr. Federico Corradi as he explores low-power spiking neural network processing systems, offering insights into energy-efficient computing for extreme-edge applications.

Social share preview for Low-power Spiking Neural Network Processing Systems for Extreme-Edge Applications

Upcoming Workshops

The TSP1 Neuromorphic Chip: Advancing Brain-Inspired Computing
Chris Eliasmith
November 11, 2025
8:00 - 9:00 EST

About the Speaker

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).

Inspired? Share your work.

Share your expertise with the community by speaking at a workshop, student talk, or hacking hour. It’s a great way to get feedback and help others learn.

Related Workshops

PEPITA - A Forward-Forward Alternative to Backpropagation

PEPITA - A Forward-Forward Alternative to Backpropagation

Explore PEPITA, a forward-forward approach as an alternative to backpropagation, presented by Giorgia Dellaferrera. Learn about its advantages and implementation with PyTorch.

The ELM Neuron: An Efficient and Expressive Cortical Neuron Model Can Solve Long-Horizon Tasks

The ELM Neuron: An Efficient and Expressive Cortical Neuron Model Can Solve Long-Horizon Tasks

Aaron tells us about the Expressive Leaky Memory (ELM) neuron model, a biologically inspired phenomenological model of a cortical neuron.

Hands-on with Xylo and Rockpool

Hands-on with Xylo and Rockpool

Discover Xylo and Rockpool in a hands-on session with Dylan Muir, exploring cutting-edge neural computation architectures and signal processing.