Seminar by Dr. Martijn Kuipers

Abstract:
Large amounts of data is generated every day by (wireless) communication systems. Most of this data is used for accounting, but it holds large amounts of meta-information. In order to optimize the systems, we are looking more and more into Artificial Intelligence (AI) and Machine Learning (ML) techniques to generate actionable insight for, for instance, QoS provisioning. 

The demand for higher datarates and lower latencies are pushing for higher spectral efficiency and for the ability to use more of the available spectrum. Whereas at the same time, the number of users is also increasing, leading to very complex wireless channels. But in order to be able to transmit data fast and accurate a precise prediction/knowledge of this wireless channel is required. Traditional methods of channel modelling can no longer cope with the high speed and accurate processing demands and we everybody is looking to AI for solutions. Deep Learning (DL) technologies are the new hot-topic in the research of physical-layer wireless communications and challenges conventional communication theories.

Another interesting segment of wireless communication, where AI is getting a lot of attention is in machine-to-machine (M2M) communication, where people are looking into decentralized nets, which can operate without the need of a complete network.

Short bio: 
Martijn Kuipers always wanted to study computer science, until a course on CDMA at the University of Delft in the Netherlands changed his ideas. He obtained the M.Sc. degree in electrical engineering from Delft University in 1999, after which he embraced a Ph.D. study at Aalborg University at the Center for Person Kommunikation, later Center for TeleInFrastruktur, and finally to CTIF GLOBAL CAPSULE ( CGC ). During the Ph.D. studies he got involved in various European project dealing with radio channels and multi carrier multiple access techniques, which also was the main topic of the doctoral research. While finishing the Ph.D. at Aalborg University in 2005, he moved to Portugal where he continued working in European projects. While still in Portugal, there was less and less time for research. In order to restore some of the fun of work, he started as an associate Professor at a local private university (Universidade Lusiada) in 2017 and has been trying to get back into some real research. This talk is part of that process.