Keynote Speaker (2)
June 15 (Tuesday) 12:00 (Central European Time)
KU Leuven – Dept. Electrical Engineering – MICAS, Leuven, Belgium
Exploiting AI in sensory devices
Sensors are embedded more and more ubiquitously into our environment. It is however impossible to swallow all this sensory data in the cloud. This requires local processing of the sensor feed in the so-called “extreme edge” nodes. This is challenge for the local nodes, which only have limited processing, memory and energy resources. This talk will give an overview of different strategies across the system stack to enable and exploit AI processing in sensory devices, ranging from low precision compute, over efficient analog processing, to complete AI-controlled adaptive sensors.
Marian Verhelst is an associate professor at the MICAS laboratories of the EE Department of KU Leuven. Her research focuses on embedded machine learning, hardware accelerators, HW-algorithm co-design and low-power edge processing. Before that, she received a PhD from KU Leuven in 2008, was a visiting scholar at the BWRC of UC Berkeley in the summer of 2005, and worked as a research scientist at Intel Labs, Hillsboro OR from 2008 till 2011. Marian is a member of the DATE and ISSCC executive committees, is TPC co-chair of AICAS2020 and tinyML2021, and TPC member VLSI and ESSCIRC. Marian is an SSCS Distinguished Lecturer, was a member of the Young Academy of Belgium, an associate editor for TVLSI, TCAS-II and JSSC and a member of the STEM advisory committee to the Flemish Government. Marian currently holds a prestigious ERC Starting Grant from the European Union and was the laureate of the Royal Academy of Belgium in 2016.