Research output per year

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Personal profile

Research interests

My research focuses on the future dynamic optical networks with flexible network functions and fast network reconfigurations. The envisioned programmable optical networks could deliver network services automatically in an on-demand approach. The flexible network resource can accommodate network requests by providing just-enough network hardware to maximize the utilisation of network resources. The margin-reduced dynamic optical network will be one of the key research themes for intelligent optical transport. To achieve this, two key research directions are explored.

Artificial Intelligence-driven optical networks

Based on the proposed SDN-based multi-layer monitoring framework, AI-based network analytics could offer novel network functions and leverage the intelligence of SDN networks. Various field trial experiments demonstrated the advantages of AI in optical networks.

Programmable multi-dimensional networks

Programmable optical hardware is one of the key enabling technologies for dynamic networks. This research will investigate programmable network architecture, reconfigurable node functions and programmable transmission equipment. Our developed architecture-on-demand synthesized optical nodes and bandwidth programmable optical transmitters provide a solid foundation for hardware-programmable optical networks. The research intends to bring programmability in multiple dimensions (i.e. TDM/WDM/SDM in optical networks). The flexibility of network hardware can adapt the capability, according to network states and network requirements, to contribute to the vision of intelligent optical transport.

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Research Output

  • 42 Conference Contribution (Conference Proceeding)
  • 25 Article (Academic Journal)
  • 2 Conference Paper
  • 1 Conference Abstract

ANN-Based Multi-Channel QoT-Prediction over a 563.4-Km Field-Trial Testbed

Gao, Z., Yan, S., Zhang, J., Mascarenhas, M., Nejabati, R., Ji, Y. & Simeonidou, D., 3 Feb 2020, In : Journal of Lightwave Technology. 38, 9, p. 2646-2655 10 p.

Research output: Contribution to journalArticle (Academic Journal)

Open Access
  • 12 Downloads (Pure)

    Dynamic Abstraction of Optical Networks with Machine Learning Technologies

    Yan, S., Gao, Z., Wang, R., Mavromatis, A., Nejabati, R. & Simeonidou, D., 16 Feb 2020, Optical Network Design and Modeling: 23rd IFIP WG 6.10 International Conference, ONDM 2019, Athens, Greece, May 13–16, 2019, Proceedings. Springer, Cham, p. 142-153 12 p. (Lecture Notes in Computer Science; vol. 11616).

    Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

  • Field Trial of Machine-Learning-Assisted and SDN-Based Optical Network Management

    Yan, S., Khan, F. N., Mavromatis, A., Fan, Q., Frank, H., Nejabati, R., Lau, A. P. T. & Simeonidou, D., 22 Apr 2019, 2019 Optical Fiber Communications Conference and Exhibition, OFC 2019 - Proceedings. Optical Society of America (OSA), 3 p. M2E.1

    Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

    Open Access
  • 4 Citations (Scopus)
    188 Downloads (Pure)


    • 1 Invited talk
    • 1 Participation in workshop, seminar, course
    • 1 Advisory work for/on national or international committee or working group

    ECOC 2018

    Shuangyi Yan (Participant)

    23 Sep 2018

    Activity: Participating in or organising an event typesParticipation in workshop, seminar, course

    Opto-Electronics and Communications Conference & Photonics in Switching and Computing 2019 (Event)

    Shuangyi Yan (Advisor)

    1 Feb 201831 Jul 2019

    Activity: Membership typesAdvisory work for/on national or international committee or working group

    IEEE Asia Communications and Photonics Conference 2017

    Shuangyi Yan (Participant)

    13 Oct 2017

    Activity: Participating in or organising an event typesInvited talk