Towards an Intelligent and Secure 5G Ecosystem for the Transformation and Digitalization of Societies Through Artificial Intelligence

Artificial intelligence (AI) has transformed our way of perceiving and interacting with technology, by providing state-of-the-art solutions for challenging problems across the tech-spectrum. The main objective of this cluster of projects is to investigate, develop, adapt, integrate and evaluate state-of-the-art machine learning (ML) techniques, which are suitable for modeling and prediction using datasets collected for complex real-world telecommunications applications. Given the applications of interest for Ericsson Inc., we will focus on ML techniques:
1. to process complex operational data (time series or high dimensional) from real time large-scale wireless and IoT networks;
2. to enable intelligent decision making and data sharing and provenance, and modeling using technologies, such as blockchain, that can scale for real-time systems;
3. for lifecycle management of operating 4G and 5G wireless networks, by addressing the need for long-term deployment, self-profiling, and anomaly detection; and
4. to augment human-computer interactions for real-time decision in support of operation and management of large-scale industrial systems.
Training ML models in such cases typically leads to complex optimization problems, using massive amounts of noisy and incomplete training data.

Faculty Supervisor:

Éric Granger;Marco Pedersoli;Chamseddine Talhi;Kaiwen Zhang;Georges Kaddoum;Kim Khoa Nguyen


Akhil Pilakkatt Meethal;Mohammad Bany Taha;Houda Khlifi;Djebril Mekhazni;Soufiane Belharbi;Paulo Freitas de Araujo Filho;Joao Victor de Carvalho Evangelista;Ha Vu Tran;Sahil Garg;Kanika Aggarwal;Bassant Selim;Alaeddine Chouchane;Wiem Badreddine


Ericsson Canada


Engineering - computer / electrical


Information and communications technologies


École de technologie supérieure



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