TALK
AI has the potential to revolutionize telecommunication networks, enhancing efficiency, automation, and decision-making. However, most AI models function as black boxes, making their integration into telecom systems inherently risky in terms of reliability and predictability. Additionally, both training and running AI models demand significant computational resources, vast datasets, and high energy consumption. This talk will explore innovative solutions to tackle these challenges, focusing on enhancing reliability and efficiency in AI-driven telecom networks. Key topics include pre-deployment calibration for ensuring AI robustness, online monitoring to detect and mitigate failures in real time, semi-supervised learning to reduce data dependency, and neuromorphic computing for energy-efficient AI processing.
WISDOM CORNER: LIVE LIFE LESSONS
Participants will have the chance to hear from Prof. Simeone about his impactful life lessons over the years as well as his advice to young researchers in the field of information and communication technologies.
Register here
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SPEAKER:
Osvaldo Simeone, King's College London, UK
Osvaldo Simeone is a professor of information engineering. He co-directs the Centre for Intelligent Information Processing Systems within the Department of Engineering of King's College London. He is also a visiting professor with the Connectivity Section within the Department of Electronic Systems at Aalborg University. He received several IEEE best paper awards, and he was awarded an Open Fellowship by the EPSRC in 2022 and a Consolidator grant by the European Research Council (ERC) in 2016. Prof. Simeone is the author of the textbook "Machine Learning for Engineers" published by Cambridge University Press, four monographs, two edited books, and more than 200 research journal and magazine papers. He is a fellow of the IET, EPSRC, and IEEE.
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MODERATOR: Ian F. Akyildiz, ITU J-FET Editor-in-Chief and Truva Inc., USA
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