Dipartimento di Informatica

Abstract: Distributed intelligence is a collaborative process to carry out different types of learning and inference tasks. Such a process enables heterogeneous and resource-constrained devices to realize diverse applications and services. This talk specifically focuses on two representative use cases of distributed intelligence in the context of mobile computing and the Internet of Things (IoT). The first one is improving user experience in mobile augmented reality through edge computing. The second use case is partitioning a pre-trained deep neural network for distributed inference in a fog network.

Short Bio: Mario Di Francesco is a Full Professor (tenured) with the Department of Computer Science at Aalto University, Finland. He received his Ph.D. degree in information engineering from the University of Pisa in 2009.
Mario was a research associate with the University of Texas at Arlington in 2009-2011 and a visiting associate research scholar at Princeton University in 2016. He received several honors in both research and teaching: best paper awards at UbiComp 2014 and the IoT conference 2015; an honorable mention at MobileHCI 2020; a Google IoT Technology Research Award in 2016; two best teacher awards from Aalto University in 2017 and 2020. Mario is an area editor of the Pervasive and Mobile Computing journal. His research interests include the Internet of Things, pervasive computing, mobile networking, and performance evaluation.