DTU Fotonik, Technical University of Denmark



Institute background

The research activities at DTU Fotonik cover a unique spectrum of central core areas within communication technology, laser technology, sensor technology, optics and materials research. DTU Fotonik is one of the only university departments in the world that cover all aspects of Photonics. Research at DTU Fotonik includes development of high speed optical communication systems, novel technologies for metro-access, and short range communication, fibre based lasers and optical enhancers, design and implementation of ultra-high-speed communications systems, development of diode lasers and diode lighting systems, development of optical sensor systems and modeling and production of advanced semiconductor based components, such as lasers and modulators. We also work with the building and administration of advanced communication networks, at back-bone as well as user levels, such a Fibre-to-the-home applications where, among other things, new compression algorithms for, for instance IPTV, are being developed.

Website – www.fotonik.dtu.dk

Key Research areas

Optical communication, Applied machine learning to photonics – Darko Zibar, dazi@fotonik.dtu.dk

Key publications

Darko Zibar, Molly Piels and Christian Schaeffer, ”Machine Learning Concepts in Optical Communication,” Journal of Lightwave Technology, vol. 34, no. 6, pp: 1442-1452, invited paper, 2016

Jakob Thrane, Jesper Weiss, Rasmus Jones, Molly Piels and Christian Schaeffer and Darko Zibar, ”Machine Learning Techniques Applied to System Characterization and Equalization,” Journal of Lightwave Technology, invited paper, to appear by the end of 2016

Darko Zibar, Luis Carvalho, Molly Piels, Andy Doberstein, Julio Diniz, Bend Nebendahl, Carolina Franciscangelis, Jose Estaran, Hansjoerg Haisch, Neil G. Gonzales, Julio Cesar, R. F. de Oliveira and Idelfonso T. Monroy, ”Application of Machine Learning Techniques for Amplitude and Phase Noise Characterization,” Journal of Lightwave Technology, vol.33, no. 7, pp: 1333- 1343, invited paper, 2015

Learning Techniques Applied to System Characterization and Equalization,” in Opti- cal Fiber Communication Conference (OFC) 2016, Anaheim, California, USA, paper, Tu3K.1, invited paper, 2016 [C5] Edson Porto da Silva, Knud J. Larsen and Darko Zibar, ”Mitigation of

Molly Piels and Darko Zibar, ”Markov chain Monte Carlo Methods for Statistical Analysis of RF Photonic Devices,” Optics Express, vol. 24, no. 3, pp: 2084-2097, 2016