The Optical Networking and Communication
Conference & Exhibition

San Diego Convention Center,
San Diego, California, USA

Innovations with Machine Learning in Optical Networks drive Process Automation

Wednesday, 6 March, 15:30-17:00
Theater II, Hall E
 

Session Description

For Machine Learning; Humans define the rules and the abstract models and constraints and the machines perform the validation steps. Then the Machine achieved results are reviewed to note they in line with what is expected. Assumption is the outcomes can be trusted due to the validation performed on the earlier, iterative model and smaller data sets. The Machines work on larger data sets that can achieve automation in the processes of configuring and provisioning an Optical Network both for today and for growth. The panel presenters will cover the human insight driven, closed loop, processes used to check and confirm the outcomes and provide their research results for the Network deployment tasks which they are wanting to Automate or have successfully delivered.

 

Speakers

Machine Learning to Automate Resource Provisioning and Failure Management
Massimo Tornatore, Associate Professor, Department of Electronics, Information and Bioengineering, ​Politecnico di Milano, Italy

 
Deep Learning for Optical Communications: Real-Time Digital Backpropagation and Beyond​
Henry Pfister, Associate Professor, Department of Electrical and Computer Engineering, Duke University, USA

 

Machine Learning in Optical Communications: Promises and Potential
Laurent Schmalen, Department Head of High-speed Systems, Signals and Processing Group, ​Nokia Bell Labs, USA
 

Biographies:

 

 
 Massimo Tornatore, Associate Professor, Department of Electronics, Information and Bioengineering, ​Politecnico di Milano, Italy 

Massimo Tornatore is currently an Associate Professor in the Department of Electronics, Information and Bioengineering at Politecnico di Milano, Italy, where he received a PhD degree in Information Engineering in 2006 and a Laurea (M.Sc. equivalent) degree in October 2001. He also holds an appointment as adjunct associate professor in the Department of Computer Science at the University of California, Davis, where he served as a postdoc researcher between 2007 and 2009. In 2005 he visited for four months the CTTC laboratories in Barcelona. He is author of about 200 peer-reviewed conference and journal papers and his research interests include performance evaluation, optimization and design of communication networks (with an emphasis on the application of optical networking technologies), cloud computing, and energy-efficient networking. His research has been developed in collaborations with industrial partners as Alcatel Lucent, Bell Labs France, France Telecom, Fastweb, Telecom Italia. He is member of the editorial board of Springer journal "Photonic Network Communications". He is member of the Technical Program Committee of various leading networking conferences as INFOCOM, OFC, ICC, Globecom, etc. He is a senior member of the IEEE and he was a co-recipient of six best-paper awards from IEEE conferences.

 

Henry Pfister, Associate Professor, Department of Electrical and Computer Engineering, Duke University, USA

 

Henry D. Pfister received his Ph.D. in electrical engineering in 2003 from the University of California, San Diego and is currently an associate professor in the Electrical and Computer Engineering Department of Duke University with a secondary appointment in Mathematics.  Prior to that, he was a professor at Texas A&M University (2006-2014), a post-doctoral fellow at the École Polytechnique Fédérale de Lausanne (2005-2006), and a senior engineer at Qualcomm Corporate R&D in San Diego (2003-2004).  His current research interests include information theory, error-correcting codes, quantum computing, and machine learning.

He received the NSF Career Award in 2008 and a Texas A&M ECE Department Outstanding Professor Award in 2010.  He is a coauthor of the 2007 IEEE COMSOC best paper in Signal Processing and Coding for Data Storage and a coauthor of a 2016 Symposium on the Theory of Computing (STOC) best paper.  He has served the IEEE Information Theory Society as a member of the Board of Governors (2019-2022), an Associate Editor for the IEEE Transactions on Information Theory (2013-2016), and a Distinguished Lecturer (2015-2016).  He was also the General Chair of the 2016 North American School of Information Theory.

 
Laurent SchmalenDepartment Head of High-speed Systems, Signals and Processing Group, ​Nokia Bell Labs, USA

 

Laurent Schmalen received both his Dipl.-Ing. degree as well as his PhD from RWTH Aachen University in Germany in 2005 and 2011, respectively. Since then, he worked as a research engineer and since 2016 also as department head at Nokia Bell Labs in Stuttgart, Germany. His work focuses on the application of forward error correcting codes, digital modulation schemes and machine learning algorithms for high-speed data transmission, in particular optical communications. Since 2014, he also serves as a guest lecturer at the University of Stuttgart. He is a senior member of the IEEE and received multiple awards for his research.

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