Prof. Soumaya Cherkaoui of Polytechnique Montréal

The evolution of future beyond 5G/6G networks is expected to rely greatly on network slicing technology. Through network slicing, communication service providers seek to meet all the requirements imposed by verticals by differentiating services and ensuring performance. Radio access network (RAN) slicing is a critical component of end-to-end network slicing, especially for ultra-reliable low-latency communication (URLLC) services.   These services are a key enabler for applications requiring near-real-time responsiveness, such as autonomous vehicles, augmented reality, and precision and mission-critical robotics. However, due to the stringent requirements of URLLC services and the dynamics of the RAN environment, slicing the RAN is a challenge.  The Open Radio Access Network (Open RAN) architecture paves the way for flexible sharing of network resources by introducing more programmability into the RAN. In addition, artificial intelligence (AI) and machine learning (ML) techniques, such as deep reinforcement learning (DRL) algorithms, are promising tools for efficient management of network resources with increased flexibility and agility.  In this talk, we will provide an overview of the use of ML for RAN slicing in an Open RAN context, as well as an overview of current challenges and open questions.

Biography:

Soumaya Cherkaoui is a Full Professor at Department of Computer and Software Engineering at Polytechnique Montréal, Canada. From 1999 to 2021, she was a professor at the department of Electrical and Computer Engineering at the Université de Sherbrooke, Québec, Canada. Before joining academia as a professor in 1999, she worked for industry as a project leader on projects targeted at the Aerospace Industry. Pr. Cherkaoui research interests lie at the convergence of communications and artificial intelligence, particularly in B5G/6G, Sustainable machine learning, Quantum Machine Learning, Federated Learning, and their applications (e.g., autonomous vehicles, smart grid, IoT, industrial IoT). Pr. Cherkaoui has held invited positions at leading institutions including the University of California at Berkeley, Monash University, and the University of Toronto, as well as an adjunct position at Lulea University, in Sweden. Pr. Cherkaoui’s work resulted in technology transfer to companies and to patented technology. She has delivered numerous keynote addresses and invited talks in the area. Pr. Cherkaoui has published over 200 research papers in reputed journals and conferences. She has been a guest editor and a member of the editorial board of several Journals including IEEE JSAC, IEEE Network, IEEE Systems and Computer Networks. Her work was awarded with recognitions and best paper awards including the Mirela Notare Award in 2023, the best paper award at IEEE LCN 2021, and a best paper award at IEEE ICC in 2017. She has chaired prestigious conferences such as IEEE LCN 2019 and has served as a symposium co-chair for flagship conferences including IEEE ICC 2018, IEEE Globecom 2018, IEEE Globecom 2015, IEEE ICC 2014, and IEEE PIMRC 2011. She was also Chair of the IEEE Communications Society Technical Committee on IoT-Ad hoc and Sensor Networks. She is a professional engineer in Canada.

Email:

Address:Polytechnique Montréal, , Montréal, Canada