AASS Seminar - The Rise of Anticipatory Multi-Objective Machine Learning

The research centre AASS arranges a seminar with Carlos Azevedo from Ericsson.

Abstract

This presentation will cover algorithmic design principles for intelligent systems exhibiting anticipatory, flexible, autonomous, and sustainable behavior. In particular, you’ll be exposed to anticipatory multi-objective machine learning strategies for automating the resolution of conflicts in sequential decision-making under multiple, conflicting, noisy, and cost-adjusted optimization criteria.

Speaker's bio

Carlos R. B. Azevedo is a Machine Intelligence and IoT Technologies researcher architecting, analyzing, and implementing intelligent networked industrial systems at Ericsson Research, Stockholm. Before joining Ericsson, he was a Research Leader in Artificial Intelligence at Samsung Research, Brazil, and served as a Postdoctoral Research at the University of Campinas, Brazil. His PhD thesis on anticipatory multi-objective machine learning was awarded in 2014 the Best Thesis National Prize in the area of Electrical, Computing, and Automation Engineering, by the Brazilian Ministry of Education.  In 2010 Carlos took part in the Global Solutions Program of Singularity University at NASA Ames Research Park, where he was engaged with a project which investigated how to augment robotic autonomy for space exploration with Artificial General Intelligence.