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 more
Meet some of our Researchers
Our most recent peer reviewed publications
Empirical study on the efficiency of Spiking Neural Networks with axonal delays, and algorithm-hardware benchmarking(2023)
Aircraft Marshaling Signals Dataset of FMCW Radar and Event-Based Camera for Sensor Fusion(2023)
PetaOps/W edge-AI µProcessors: Myth or reality?(2023)
Accurate online training of dynamical spiking neural networks through Forward Propagation Through TimeNature Machine Intelligence (2023)