Online Seminar with Prof. Adnan Shahid for Wireless Foundation Models
Artificial Intelligence (AI) plays a crucial role in the evolving landscape of wireless communications, addressing challenges that traditional approaches cannot solve. This talk discusses the evolution of wireless AI, emphasizing the transition from isolated, task-specific models to more generalized and adaptable AI models, inspired by the recent success of large language models (LLMs). To overcome the limitations of task-specific AI strategies in wireless networks, Wireless Foundation Models are proposed. The concept of Wireless Foundation Models is to create generic models trained on wireless data (e.g., IQ signals, RSSI, network KPIs) that can be applied to a variety of tasks such as interference detection, activity detection, power allocation, channel estimation, and more.
To realize this vision, several key challenges must be addressed, such as identifying effective pre-training tasks, supporting embedded time-series data, and enabling human-
understandable interaction. Furthermore, it is essential for Wireless Foundation Models to interact with LLMs, which can assist in extracting meta-data (such as classifications, semantic description of the wireless network conditions, sensing applications, human behavior, etc.) from these models. This integration with LLMs can lead to continuous optimization of wireless networks.
Date and Time
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- Date: 16 Apr 2025
- Time: 12:00 PM UTC to 01:00 PM UTC
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- Starts 13 April 2025 11:00 PM UTC
- Ends 16 April 2025 12:59 PM UTC
- No Admission Charge
Speakers
Adnan of Ghent University
Wireless Foundation Models
Biography:
Adnan Shahid (M’15 - SM’17) received the B.Sc. and M.Sc. degrees in computer engineering from the University of Engineering and Technology, Taxila, Pakistan, in 2006 and 2010, respectively, and the Ph.D. degree in information and communication engineering from Sejong University, South Korea, in 2015. From Mar 2015 to Aug 2015, he worked as a Postdoctoral Researcher at Yonsei University, South Korea. Following that, from Sep 2015 to Jun 2016, he worked as an Assistant Professor at Taif University, Kingdom of Saudi Arabia. Currently, he is Professor in the Internet Technology and Data Science Lab (IDLab) of Ghent University and imec. He is the Secretary and a Voting Member of IEEE P1900.8 (active PAR)— Standard for Training, Testing, and Evaluating Machine-Learned Spectrum Awareness Models. He has been involved in several projects such as DARPA Spectrum Collaboration Challenge (SC2), European H2020 (eWINE, WiSHFUL), and ESA (CODYSUN, MRC100). He is currently leading several European and national projects (imec ICON, FWO). Within IDLab-intelligent Wireless Networking (iWINe), he leads the 'AI/ML for Wireless' subgroup. His research interests include machine learning and artificial intelligence for wireless communications and networks, Wireless Foundation Models, localization, connected healthcare, etc.
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