Abstract: Communicating tactile-haptic sensations such that humans can immersively interact with distant real/virtual environments through machines/robots, i.e., H2M communication, is a fascinating but challenging leap to our current networks. The optical fiber access network, as a pillar of support for low-latency applications, will need continuous capacity upgrading and latency reduction for succeeding H2M communications. The required improvement could partly be made with the rapid-advancing machine learning (ML) techniques to innovate network control solutions. In this talk, we will go through how intelligent bandwidth decisions can be driven by ML to support tactile H2M communications over optical access networks.
Speaker: Lihua Ruan received her Ph.D. from the University of Melbourne (UoM), Australia, in 2020. In Mar 2019 and April, 2019, she was a visiting student at Massachusetts Institute of Technology (MIT), USA. From 2020 to 2022, she was a Postdoctoral Fellow at the Chinese University of Hong Kong, Shenzhen, China. She is currently a Researcher at Pengcheng Laboratory, Shenzhen. Lihua pursues a research passion on fiber-wireless access networks, machine learning for networks, tactile Internet and low-latency communications, and wireless sensing and security. Lihua actively serves as a reviewer of many high-rank journals and is/was on the Technical Program Committee (TPC) of OFC, IEEE ICC, and ACP conferences. She was a guest editor for Elsevier Computer Networks Special Issue and was invited for talks in 2024, 2023 ICOCN and 2024 OECC.
Sponsors: IEEE Photonics Society PCJS Chapter
Zoom: https://futurewei.zoom.us/j/6135444997
Zoom ID: 613 544 4997
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