Our long-term research goal is to enable intelligence inside our microchips by designing neuromorphic circuits and systems that mimic the brain's fundamental information processing strategies for solving challenging real-world problems.
We aim to build brain-inspired machine intelligence devices. We address the problem of machine intelligence across the whole computing stack, from new models of computation down to hardware. We take inspiration from the brain's efficiency, and we research neural-inspired models of computation that are massively parallel, compute on-demand, and benefit from emerging nano- and microelectronics technologies to develop new disruptive neuromorphic computing systems.
Read moreMeet some of our Researchers
Recent Publications
Our most recent peer reviewed publications
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An Implantable Neuromorphic Sensing System Featuring Near-Sensor Computation and Send-on-Delta Transmission for Wireless Neural Sensing of Peripheral Nerves
IEEE Journal of Solid-State Circuits (2022) -
Attentive Decision-Making and Dynamic Resetting of Continual Running SRNNs for End-to-End Streaming Keyword Spotting
(2022) -
An Event-Driven Recurrent Spiking Neural Network Architecture for Efficient Inference on FPGA
(2022) -
Evolved neuromorphic radar-based altitude controller for an autonomous open-source blimp
(2022) -
Radar Perception for Autonomous Unmanned Aerial Vehicles
DroneSE and RAPIDO 2022 (2022)
Contact
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Visiting address
Flux, room 4.130Department of Electrical Engineering5612 AP EindhovenNetherlands -
Teamleadf.corradi@ tue.nl