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Machine learning is very popular nowadays for solving problems in many fields, including wireless networks such as 5G networks that we use to make calls and connect to the internet using our phones. Next-generation wireless networks (NGWNs), such as 6G networks, will include more diverse devices and applications that make them more complex to control, even using machine learning approaches. In my Ph.D. thesis, I addressed some of the practical challenges of applying machine learning approaches, specifically reinforcement learning, in real deployments of NGWNs.

For upcoming interviews check out the Grad Chat webpage on Queen’s University School of Graduate Studies & Postdoctoral Affairs website

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