Time: 10:00 Am-11:30 Am, Friday, June 9th, 2023

Venue: E10-211, Yunqi Campus

Host: Dr. Mohamad Sawan, Chair Professor, School of Engineering

Language: English

Speaker：

Prof. Giacomo Indiveri

Professor

University of Zurich and ETH Zurich

Biography:

Giacomo Indiveri is the director of the Institute of Neuroinformatics of the University of Zurich (UZH) and ETH Zurich and a dual Professor of Neuromorphic Cognitive Systems at UZH and ETH Zurich. He obtained an M.Sc. degree in electrical engineering in 1992 and a Ph.D. degree in computer science in 2004 from the University of Genoa, Italy.

His research interests lie in the study of spike-based learning mechanisms and recurrent networks of biologically plausible neurons, and in their integration in real-time closed-loop sensory-motor systems designed using analog/digital circuits and emerging memory technologies. His group uses these neuromorphic circuits to validate brain inspired computational paradigms in real-world scenarios, and to develop a new generation of faulttolerant event-based neuromorphic computing technologies. Indiveri is senior member of the IEEE society, and a recipient of the 2021 IEEE Biomedical Circuits and Systems Best Paper Award. He is also an ERC fellow, recipient of three European Research Council grants.

Abstract:

Artificial computing systems are vastly outperformed by biological neural processing ones for many practical tasks that involve sensory perception and real-time interactions with the environment, especially when size and energy consumption are factored in. One of the reasons is that biological neural processing systems, which comprise billions of neurons that communicate in parallel mainly via asynchronous action potentials, are very different from today's artificial computing systems, based mainly on serial communication and synchronous logic. In this presentation I will present brain-inspired biologically plausible circuits and processing systems, comprising networks of spiking neurons implemented in mixed-signal analog/digital VLSI technology, for performing state-dependent computation and solving constrain-satisfaction problems. The presentation will begin with an introduction to motivate the approaches presented, followed by a basic description of the circuits and networks used, and a demonstration of applications and problems that can be solved following this approach.

Contact:

Ms. Huaiwei Shi, School of Engineering

shihuaiwei@westlake.edu.cn