Biography
Philippe Dierickx joined Bell Labs in 2020 and currently working in the department of Autonomous Networks within Nokia Bell Labs Solution Research, Antwerp (Belgium). He specialized in DSL channel frequency (Hlog) and reflectrometry (SELT) interpretation using Deep Learning advanced techniques. His latests researches focus on traffic decomposition of an Access Network. Prior to Bell Labs, from 1999 until 2015, within Alcatel-Lucent, he evolved from L2 support engineer to people manager of a L3 support team for worldwide support of Intellingent Networks. From 2015 until 2020, as part of Nokia Motive Network Analyzer team, he started developping dedicated algorithms to detect problematic copper access line in DSL networks, then moved to Deep Learning methods to significantly improve the detection results.
- M.Sc. degree in Industrial Engineering in electricity, electronics and telecommunications from ECAM Brussels
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Comparison Between CNN, ViT and CCT for Channel Frequency Response Interpretation and Application to G.Fast. Philippe Dierickx; Axel Van Damme; Nicolas Dupuis; Olivier Delaby IEEE Access Volume 11 DOI: 10.1109/ACCESS.2023.3247877
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EP3128728 & US10264117 : Method and device for detecting a broken binder
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EP3399694 : Method and device for assessing a qos of data communication systems
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EP3451642 & US11089150 : Method and network analyzer of evaluating a communication line
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EP3562047 : Method of training a deep neural network classifier, a training module and a network analyzer
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EP3691186 & US10812206 : Method and apparatus for predicting the bitrate of a repaired communication channel
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EP3863269 & US20210250062 : Method and apparatus for monitoring a communication line
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EP4125245 & US20230032603 : Apparatus and method for generating an estimate of a channel frequency response
- Jun 2018 : Nokia "Most innovative AI solution Award"
- Dec 2019 : Nokia AI “Future X network” award
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