Machine Learning in Optical Networks

Session 1: Securing critical infrastructures with network automation: the AI-NET PROTECT perspective

Organizers

Christoph Lipps (German Research Center for Artificial Intelligence, Germany)

Paolo Monti (Chalmers University of Technology, Sweden)

Lena Wosinska (Chalmers University of Technology, Sweden)

List of talks

Optical Performance Monitoring in Digital Coherent Communications: Intelligent Error Vector Magnitude Estimation,” Yuchuan Fan, Oskars Ozoliņš (RISE, Sweden)

Leveraging Big Data Pipeline to Enhance Security in SDN networks,” Amirreza Fazely Hamedani (Gesellschaft für wissenschaftliche Datenverarbeitung mbH Göttingen, Germany)

Machine Learning-based Optical Spectrum Analysis for Soft-Failure Prediction,” Lars E. Kruse (Christian-Albrechts-University of Kiel, Germany)

Enabling the Sixth Generation (6G) Wireless Systems: A Security Perspective on Wireless Optical Communication,” Christoph Lipps (German Research Center for Artificial Intelligence, Germany)

Resource-efficient monitoring of physical layer breaches,” Marija Furdek (Chalmers University of Technology, Sweden)

Signatures from eavesdropping SM or MM fibre,” Stefan Karlsson (Swedish Defence Material Administration, Sweden)

Session 2: Machine Learning in optical networks roadmap: chart out applications and needs

Organizers: IEEE Future Networks Optics WG

Zuqing Zhu (University of Science and Technology of China, China)

Francesco Musumeci (Politecnico di Milano, Italy)

Lena Wosinska (Chalmers University of Technology, Sweden)

Daniel Kilper (Trinity College Dublin, Ireland)

List of talks

Francesco Giacinto Lavacca (University of Rome “La Sapienza”, Italy)
“AI-based algorithms applied to C-RAN Functional Splitting and Advanced Antenna Systems Problem”

Omran Ayoub (University of Applied Sciences and Arts of Southern Switzerland, Switzerland)
“Detecting and Explaining Bias in ML Models for Optical Networks”

Brigitte Jaumard (Concordia University, Canada)
“Machine Learning for Cognitive Optical Networks”

Zuqing Zhu (University of Science and Technology of China, China)
“Machine Learning in and for Optical Data Center Networks”

Darko Zibar (Technical University of Denmark, Denmark)
“How can machine learning enabled programmable optical amplifiers reduce power consumption of optical networks”

Andrea Sgambelluri (Scuola Superiore Sant’Anna, Italy)
“Data Collection and Machine Learning solutions for Soft-failure Detection in Optical Networks”

Lareb Zar Khan (Scuola Superiore Sant’Anna, Italy)
“Data-centric view of machine learning for optical network failure management”

Daniel Kilper (Trinity College Dublin, Ireland)
“Charting a roadmap for machine learning in optical networks”

Panel Discussion

Duration of each session: 2h

Important Dates

Submission deadline (firm): 20 Dec. 2022; 20 Jan. 2023; 27 January 2023

Acceptance notification: 10 March 2023

Camera-ready submission: 20 March 2023

Conference date: 08-11 May 2023

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