Shuangyi Yan

Shuangyi Yan

Senior Lecturer in High Performance Networking & Optical Network

High Performance Networks Group, Smart Internet Lab, University of Bristol

Biography

Dr Shuangyi Yan is a Senior Lecturer in the High Performance Networks Group in the Smart Internet Lab at the University of Bristol. He received the B.E degree in information engineering from Tianjin University, Tianjin, China in 2004. In 2009, he got the PhD degree in Optical Engineering from Xi’an Institute of Optics and Precision Mechanics, CAS, Xi’an, China. From 2011 to 2013, Dr Yan worked in the Hong Kong Polytechnic University, Hong Kong, as a postdoctoral researcher, investigating on the spectra-efficient long-haul optical transmission system and low-cost short-range transmission system. In July 2013, he joined the University of Bristol. His research focuses on machine-learning applications in dynamic optical networks and 5G Beyond networks, programmable optical networks, and data centre networks. He is the author or co-author of over 80 refereed publications, of which include several post-deadline papers in optical communication related top-level conferences. Dr Yan has delivered 9 invited talks in relevant conferences, such as Optical Networking and Communication Conference (OFC 2019), Optical Network Design and Modelling (ONDM 2019 & 2018), ECOC 2018, and Asia Communications and Photonics Conference (ACP 2017). He also served as Technical Program Committee members and Co-Chairs in several conferences, such as EuCNC, ONDM, OECC, and ACP.

Interests

  • Artificial Intelligence in Optical Networks
  • Automatic programmable networks
  • 5G and Beyond Networks

My Teaching Activities

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Software-Defined Networking over Raspberry Pis

The aim of this unit is to give students a practical introduction to digital logic design and prototyping in FPGAs based on VHDL entry, using industry standard tools. Students will work in groups to design a functioning digital system and implement it.

Digital Design Group

The aim of this unit is to give students a practical introduction to digital logic design and prototyping in FPGAs based on VHDL entry, using industry standard tools. Students will work in groups to design a functioning digital system and implement it.

Data Centre Networking

Architecture for Data Centres

Projects

5G-Clarity Project

5G-CLARITY will develop and demonstrate a beyond 5G system for private networks integrating 5G, Wi-Fi, and LiFi technologies, and managed through AI based autonomic networking.

Meet the Team

Principal Investigators

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Shuangyi Yan

Senior Lecturer in High Performance Networking & Optical Network

Artificial Intelligence in Optical Networks, Automatic programmable networks, 5G and Beyond Networks

PhD Students

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Hilary Frank

PhD Researcher (Sep 2018~ Now)

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Xueqing Zhou

PhD student (2019.10 ~ Now)

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Shen Sen

PhD student (2020.10 ~ Now)

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Ruizhi Yang

PhD student (2020.1 ~ Now)

Alumni

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Zhengguang Gao

Previous Visiting Researcher (Nov 2018~Nov 2019)

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Paurakh Paudyal

Previous Final-Year student (2019~ 2020)

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Lida Liu

Previous Visiting Researcher (April 2019~Sep 2019)

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Dr Xi Chen

Previous Visiting Researcher (Jan 2019~Jan 2020)

Recent & Upcoming Talks

Machine Learning Applications for 5G and Beyond

Invited talk about Machine Learning Application in 5G and Beyond Networks. In the report, I discussed the novel networking concepts in 5G and the corresponding challenges that require the adoption of Machine Learning based applications. Thanks to 5G-Clarity project, we are developping new research direction with a well-trained team, deep understanding of 5G networking, simulation and emulation platform, and the 5G UK testbed.

Recent Publications

Quickly discover relevant content by filtering publications.
(2021). Toward Deployments of ML Applications in Optical Networks. IEEE Photonics Technology Letters.

DOI

(2021). Distributed Abstraction and Verification of an Installed Optical Fibre Network. Scientific Reports.

DOI

(2021). A Programmable ROADM System for SDM/WDM Networks. Applied Sciences.

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(2021). Deep Reinforcement Learning-Based Policy for Baseband Function Placement and Routing of RAN in 5G and Beyond. Journal of Lightwave Technology.

DOI

(2020). An Efficient Hardware Generator for Massive Non-Stationary Fading Channels. IEEE Global Communications Conference.

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