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Chiara Bartolozzi

Senior Researcher Tenured - Principal Investigator
Event-Driven Perception for Robotics
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Chiara Bartolozzi is Researcher at the Italian Institute of Technology. She earned a degree in Engineering at University of Genova (Italy) and a Ph.D. in Neuroinformatics at ETH Zurich, developing analog subthreshold circuits for emulating biophysical neuronal properties onto silicon and modelling selective attention on hierarchical multi-chip systems.

She is currently leading the Event-Driven Perception for Robotics group, with the aim of applying the "neuromorphic" engineering approach to the design of robotic platforms as enabling technology towards the design of autonomous machines.

This goal is pursued by inducing a paradigm shift in robotics, based on the emerging concept of Event-Driven (ED) sensing and processing. Similarly to their biological counterpart, and differently from traditional robotic sensors, ED sensory systems sample their input signal at fixed (and relative) amplitude changes, intrinsically adapting to the dynamics of the sensory signal: temporal resolution is extremely high for fast transitory signals and decreases for slower inputs.

This approach naturally leads to better robots that acquire, transmit and process information only when needed, optimising the use of resources, leading to real-time, low-cost, operation.

Chiara has participated to a number of EU funded projects, she is currently coordinating the European Training Network "NeuTouch", where 15 PhD students are studying how touch perception works in humans and animals, in order to develop artificial touch perception systems for robots and hand prosthesis. As leader of the educational activities of the coordination and support action NEUROTECH, she is co-organising the Neuromorphic Colloquium, a series of online events to build up educational material for the next generation of neuromorphic researchers.

She is an IEEE member, actively supporting the CAS and RAS societies. In 2020, she has co-chaired "AICAS2020", on Circuits and systems for efficient embedded AI.