时间：2023年7月20日（周四）下午15:00-17:00
地点：第一馆113会议室
线上链接：腾讯会议553-990-625
报告题目：Mixed-signal neuromorphic circuits for bio-signal processing applications
报告人：Giacomo Indiveri教授，苏黎世大学与苏黎世联邦理工学院终身教授、苏黎世神经信息研究所 INI 所长
报告简介：
For many edge-computing tasks that require real-time processing of sensory data and closed-loop interactions with the environment, conventional ANN accelerators cannot match the performance and efficiency of animal brains. One of the reasons for this gap is that neural computation in biological systems is organized in a way that is very different from the way it is implemented in today's deep network accelerators. In addition to being naturally event driven and asynchronous, neural computation in biological systems is tightly linked to the physics of their computing elements and to their temporal dynamics. Mixed-signal brain-inspired hardware architectures that emulate the biophysics of real neurons and synapses represent a promising technology for implementing alternative computing paradigms that bridge this gap.In this talk I will present hybrid analog/digital electronic circuits that directly emulate the biophysics of neural systems and present brain-inspired routing schemes multi-core architectures that support small-world network connectivity and minimize memory requirements.
报告人简介：
Giacomo Indiveri is leading the Neuromorphic Cognitive Systems group at the Institute of Neuroinformatics of the University of Zurich and ETH Zurich. Indiveri graduated in electrical engineering from the University of Genoa, Italy in 1992, worked as a Postdoctoral fellow with Prof. Christof Koch, in the Dept. of Biology at the California Institute of Technology from 1994 to 1996 and joined the Institute of Neuroinformatics in 1996.
Indiveri obtained his Habilitation at ETH Zurich on Neuromorphic Engineering in 2006 and was awarded an ERC starting grant in 2011.Engineer by training, Indiveri has always been interested also in physics, computer science, and neuroscience. He is combining these disciplines by studying real and artificial neural processing systems, and by building hardware neuromorphic cognitive systems, using full custom analog and digital VLSI technology.
报告题目：Neuromorphic Navigation and Obstacle Avoidance
报告人：Elisabetta Chicca教授，荷兰格罗宁根大学终身教授
报告简介：
Animals have evolved mechanisms to travel safely, fastly, and efficiently within a variety of habitats. On a journey in dense terrains containing trees, branches, stems, or human-made buildings, animals must avoid collisions and sometimes cross narrow passages while controlling an overall course toward a target destination. To date, multiple hypotheses address how animals solve different challenges faced during such travel. In this talk we show that a single mechanism leads to obstacle avoidance and enables safe, fast, and efficient travel in dense terrains. We developed a robotic system inspired by the behaviours and neurobiology of insects which integrates obstacle avoidance with straight line navigation. Our neuromorphic agent has remarkable capabilities for travelling in dense terrains, avoiding collisions, crossing narrow gaps, selecting safe passages, and maintaining a safe distance to objects. At the same time it is able to keep track of the difference between current and desired heading to successfully performs straight line navigation in a variety of dense environments. Our findings provide a working hypothesis for how straight line navigation and obstacle avoidance could take place in insects, bringing us one step closer towards understanding the insect brain. Furthermore, our system illustrates that we can design novel hardware systems, possibly inheriting the efficiency of animals, by understanding the underlying mechanisms navigation behaviour.
报告人简介：
Elisabetta Chicca obtained a "Laurea" degree (M.Sc.) in Physics from the University of Rome 1 "La Sapienza", Italy in 1999 with a thesis on CMOS spike-based learning. In 2006 she received a Ph.D. in Natural Science from the Swiss Federal Institute of Technology Zurich (ETHZ, Physics department) and in Neuroscience from the Neuroscience Center Zurich. E. Chicca has carried out her research as a Postdoctoral fellow (2006-2010) and as a Group Leader (2010-2011) at the Institute of Neuroinformatics (University of Zurich and ETH Zurich) working on development of neuromorphic signal processing and sensory systems.
Between 2011 and 2020 she lead the Neuromorphic Behaving Systems research group at Bielefeld University (Faculty of Technology and Cognitive Interaction Technology Center of Excellence, CITEC). In 2021 she established the Bio-Inspired Circuits and Systems group at the University of Groningen. Her current interests are in the development of CMOS models of cortical circuits for brain-inspired computation, learning in spiking CMOS neural networks and memristive systems, bio-inspired sensing (vision, touch, olfaction, audition, active electrolocation) and motor control. She combines these research approaches with the aim of understanding neural computation by constructing behaving agents which can robustly operate in real-world environments.
