Research interest

My research focus is on brain-inspired event-driven algorithms and networks that process useful events in the natural world and the mapping of these networks onto energy-efficient VLSI chips and embedded systems. The aim is to develop real-time sensory computing systems that learn novel features centered around the sparse asynchronous and correlated spike information from neuromorphic sensors such as the silicon DVS retina and the AEREAR2 cochlea. We implement neural electronic equivalents of these algorithms in FPGA or in custom silicon, for example, spiking deep networks, and custom aVLSI silicon dendritic circuits.  We hope to develop an understanding of some of the principles used in our brains for robust processing of real-time information. Our recent designs integrate event-driven deep recurrent neural networks together with the event-driven outputs of the audio sensors and are used to produce demonstrators of real-time audio edge devices for tasks such as keyword spotting and simple speech recognition.

• Liu Google Scholar Page

• Shih-Chii Liu Publications

Biography

I did my Ph.D. in the Computation and Neural Systems Program at California Institute of Technology under the supervision of Dr. Carver Mead. For my doctoral thesis, I studied models of motion processing in the fly visual system and implemented the subsequent models in silicon. Prior to that, I worked at the Rockwell Research International Laboratories in Thousand Oaks on various neuromorphic systems for commercial purposes. I also received a M.Sc. degree in Electrical Engineering at UCLA and a B.Sc. degree in Electrical Engineering at Massachusetts Institute of Technology. In between my B.Sc. and M.Sc., I worked at different companies in Silicon Valley.

After receiving my Ph.D, I stayed for one year as a Lecturer at Caltech before moving to the Institute of Neuroinformatics in Zurich. I am currently an Adjunct Professor in the Faculty of Science at the University of Zurich.

Further details of the CV are here.