Ahmad Nagib (computing) – Building Trust in Reinforcement Learning for Next-Generation Wireless Networks episode artwork

EPISODE · Feb 18, 2025 · 35 MIN

Ahmad Nagib (computing) – Building Trust in Reinforcement Learning for Next-Generation Wireless Networks

from Grad Chat - Queen's School of Graduate Studies and Postdoctoral Affairs · host CFRC Podcast Network

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

Episode metadata supplied by the publisher feed · Published Feb 18, 2025

Embed this episode

NOW PLAYING

Ahmad Nagib (computing) – Building Trust in Reinforcement Learning for Next-Generation Wireless Networks

0:00 35:37

No transcript for this episode yet

We transcribe on demand. Request one and we'll notify you when it's ready — usually under 10 minutes.

No similar episodes found.

No similar podcasts found.

Frequently Asked Questions

How long is this episode of Grad Chat - Queen's School of Graduate Studies and Postdoctoral Affairs?

This episode is 35 minutes long.

When was this Grad Chat - Queen's School of Graduate Studies and Postdoctoral Affairs episode published?

This episode was published on February 18, 2025.

Can I download this Grad Chat - Queen's School of Graduate Studies and Postdoctoral Affairs episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.
URL copied to clipboard!