Mar 08, 2019 | 15:00—16:00
The emergence of ubiquitous sensing and control of the physical world through networks of embedded computing devices has currently gone beyond conventional areas of ambient and environmental monitoring and reached the cost-sensitive, generally risk averse and safety critical industrial domain. Data-driven models have been deployed for process fault detection and diagnosis, improving yields of production lines and optimisation of key performance indicators such as energy efficiency and maintenance and productivity related metrics, with outreaching social and environmental impact. The talk aims to discuss the current context and challenges related to the design, implementation and evaluation of advanced data processing and learning algorithms in industry applications. Special focus is given to in situ efficient inference on distributed embedded devices by means of novel deep neural network architectures.
Grigore Stamatescu is Associate Professor at the University Politehnica of Bucharest, Romania and a Visiting Research Scientist at the Complexity Science Hub and the Technical University of Graz. His current research interests span the areas of networked embedded sensing, the internet of things and distributed information processing in industry, the built environment and smart city applications, with more than 100 publications in international journals and conference proceedings. He was a 2015-2016 Fulbright Visiting Scholar and he is a current recipient of the Joint Excellence in Science and Humanities grant of the Austrian Academy of Sciences. Grigore Stamatescu is member of the IEEE Robotics and Automation Society, ACM and the IFAC TC 3.3. Telematics: Control via Communication Networks.