FONTE-EID

Mini-Symposium: ‘ML Techniques and Challenges’

This Mini-symposium is led by MENTOR and co-organised jointly by the MSCA projects FONTE, REAL-NET and POST-DIGITAL, all coordinated by Aston Institute of Photonic Technologies (AiPT).

The aim of this mini-symposium is increasing the ESRs’ knowledge in machine learning and the research challenges machine learning presents. There will be Q&A sessions after every talk, with high level discussions.

 

24th November 2021,  online

All times are CET, Paris, Berlin, Rome time.

A participation link has been emailed.

 

9:50-10:00	Opening Remarks
10:00 – 11:00	Prof. Darko Zibar Technical University of Denmark (DTU), Denmark Optimum phase measurement in the presence of noise
11:00 – 11:15	Break
11:15 – 12:15	Prof. Magnus Karlsson Chalmers University of Technology, Sweden Modulation and shaping in optical communications
12:15 – 14:00	Lunch
14:00 – 15:00	Prof. Vittorio Curri Polytechnic University of Turin, Italy Experimental results summary on using ML at the physical layer in synergy with GNPy
15:00 – 15:15	Break
15:15 – 16:15	Associate Prof. Andrea Carena Polytechnic University of Turin, Italy ML applications to optical systems and devices: from the design of Raman amplifiers to the management of NxN switches
16:15 – 16:30	Closing

 

SPEAKERS

Darko Zibar is Professor at the Department of Photonics Engineering, Technical University of Denmark and the group leader of Machine Learning in Photonics Systems (M-LiPS) group. He received M.Sc. degree in telecommunication and the Ph.D. degree in optical communications from the Technical University of Denmark, in 2004 and 2007, respectively. He has been on several occasions (2006, 2008 and 2019) visiting researcher with the Optoelectronic Research Group led by Prof. John E. Bowers at the University of California, Santa Barbara, (UCSB). At UCSB, he has been working on topics ranging from analog and digital demodulation techniques for microwave photonics links and machine learning enabled ultra-sensitive laser phase noise measurements techniques. In 2009, he was a visiting researcher with Nokia-Siemens Networks, working on clock recovery techniques for 112 Gb/s polarization multiplexed optical communication systems. In 2018, he was visiting Professor with Optical Communication (Prof. Andrea Carena, OptCom) group, Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino working on the topic of machine learning based Raman amplifier design. His resrearch efforts are currently focused on the application of machine learning technqiues to advance classical and quantum optical communication and measurement systems. Some of his major scientific contributions include: record capacity hybrid optical-wireless link (2011), record sensitive optical phase noise measurement technique that approaches the quantum limit (2019) and design of ultrawide band arbitrary gain Raman amplifier (2019). He is a recipient of Best Student paper award at Microwave Photonics Conference (2006), Villum Young Investigator Programme (2012), Young Researcher Award by University of Erlangen-Nurnberg (2016) and European Research Council (ERC) Consolidator Grant (2017). Finally, he was a part of the team that won the HORIZON 2020 prize for breaking the optical transmission barriers (2016).