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ITU Journal Webinars Series

The ITU Journal launched its new series of webinars to present insights and forward-looking research on future and evolving technologies. The webinars of this series feature industry leaders and highly cited professors who will share their pioneering studies and visions, as well as their impactful life lessons learned over the years.

The webinars are open to anyone interested in the topics, free of charge. More information, including registration, is available on each event's website.
[Invitation letter]

Watch the recordings and subscribe to the ITU Journal Webinars Series playlist on YouTube: WATCH ALL WEBINARS

23 April 2024

This webinar will introduce some of Prof. Qian Zhang’s work related to how to leverage the wearables and the communication medium's sensing capability to enable smart healthcare applications, especially focusing on home care scenario.

24 April 2024

This webinar will present T-Mobile’s innovations in 5G network that have set the company up to deliver upon aggressive targets, including new lines of business like FWA and network slicing, among others.

30 April 2024

This webinar will discuss how to achieve the delicate equilibrium of deploying AI systems that can harmoniously integrate transparency, privacy, and performance requirements.

7 May 2024

The price of distributed machine learning

This webinar will discuss the hurdles of distributed Machine Learning (ML) and how they can be solved by leveraging dynamic structures of ML models which already exists as well as techniques for the compression of ML models and input datasets.

4 June 2024

After introducing VisionX, this webinar will highlight the importance of transmitting semantic information as opposed to raw data that is either redundant, stale or useless to a receiver to carry out a task.

11 June 2024

This webinar investigates the challenges of deploying generative Artificial Intelligence (AI) at the edge to enhance privacy and efficiently use network and computational resources. It addresses the challenges of implementing efficient distributed learning for generative AI applications, such as Large Language Models.

Past webinars - I

Machine learning at the wireless edge
H. Vincent Poor, Princeton University, USA
Edge AI networks: Challenges and opportunities
Mérouane Debbah, CentraleSupélec and TII, France and UAE
Information and communication theory with biochemical and molecular components for biological sensing and control
Massimiliano Pierobon, University of Nebraska-Lincoln, USA
6G and the metaverse will power a holographic society
Mischa Dohler, Ericsson Inc., USA
Semantic communications: Transmitting beyond bits
Zhijin Qin, Queen Mary University of London, UK
Ultrabroadband communication and networking solutions to unleash the Terahertz Band
Josep Miquel Jornet, Northeastern University, USA
The journey from 5G to 6G: Toward a well-being society
Naoki Tani, NTT DOCOMO, Japan
AI, machine learning RAN intelligent controller for 6G
Alex Jinsung Choi, O-RAN Alliance, Germany
Transformation in the 5G era
Alex Sinclair, GSMA, United Kingdom
A peek into the deep convergence towards 6G
Chih-Lin I, China Mobile Research Institute, China

Past webinars - II

Wireless networking, security, and sensing above 100 GHz
Edward W. Knightly, Rice University, USA
AI-EDGE: Designing future XG networks and distributed intelligence
Ness B. Shroff, The Ohio State University, USA
Deviation from the standard - Toward opening up 5G telecommunications
Muriel Médard, Massachusetts Institute of Technology, USA
Disrupting NextG
Andrea J. Goldsmith, Princeton University, USA
Creating the foundation for 6G: Laying the groundwork for the network of the future
Nishant Batra, Nokia USA
Aimed at transformation: Telecom network technology development
Wang Xiaoyun, China Mobile, China
Unlocking new capacity in 6G cellular systems via site-specific ML-aided design
Jeffrey Andrews, The University of Texas at Austin, USA
Waste Figure (W): A figure of merit for the power-efficient ("green") engineering of any device or cascade of circuits and systems
Theodore Rappaport, New York University, USA
Decoding hidden worlds: Unprecedented sensing and connectivity for climate, robotics and smart environments
Fadel Adib, Massachusetts Institute of Technology, USA