The Efficient circuits & systems for Machine Intelligence (EMI) research lab focuses on designing energy-efficient digital AI hardware for edge computing, emphasizing ultrahigh-speed communication, video/audio processing, robotics, and biomedical applications. We aim to bridge the gap between artificial neural networks (ANNs) and spiking neural networks (SNNs) by applying brain-inspired neuromorphic principles to massively accelerate the computation of state-of-the-art deep neural network (DNN) architectures while maintaining competitive accuracy on real-world tasks (We are hiring!).

August 29, 2022

We congratulate Dr. Qinyu Chen again for winning the BRIDGE Proof of Concept grant for her postdoctoral project. The 130,000 CHF fund will be released by the Swiss National Science Foundation (SNSF) and Innosuisse - Swiss Innovation Agency. The EMI lab will collaborate with Dr. Qinyu Chen, a Postdoctoral Researcher in the Sensors Group at the Institute of Neuroinformatics, University of Zurich and ETH Zurich to build next-generation edge AI chips for healthcare.

August 17, 2022

We congratulate Dr. Qinyu Chen and other co-authors for publishing the paper "Cerebron: A Reconfigurable Architecture for Spatio-Temporal Sparse Spiking Neural Networks" in the IEEE Transactions on Very Large Scale Integration Systems (TVLSI). See our paper at this link.

Chang Gao, Tobi Delbruck, Shih-Chii Liu

IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

[Journal Paper Link] [Preprint Link] [Code Link]

Kwantae Kim*, Chang Gao*, Rui Graça, Ilya Kiselev, Hoi-Jun Yoo, Tobi Delbruck, Shih-Chii Liu

2022 International Solid-State Circuits Conference (ISSCC) & IEEE Journal of Solid-State Circuits (JSSC)

[Conference Paper Link] [Journal Paper Link] [Preprint Link]