Lionel Gueguen
Principal Applied Scientist at Amazon
Denver Metropolitan Area United States
Summary
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SeniorLionel Gueguen is a Principal Applied Scientist with nine years of industry experience and a deep specialization in computer vision and large-scale remote sensing. He has led ML and perception efforts at Amazon and Uber, translating research-grade image and time-series techniques into production systems for mapping, autonomous perception, and rapid disaster assessment. His background includes designing pipelines that handle hundreds of terabytes of satellite data and novel methods for indexing and compressing image time series from his PhD work. Known internally as a "master of gradients," he combines rigorous academic roots with pragmatic engineering to ship robust, scalable models. Based in the Denver area, he brings a rare blend of remote-sensing domain knowledge and hands-on ML deployment experience that accelerates product impact.
10 years of coding experience
14 years of employment as a software developer
French, Spanish, Italian, English
Github Skills (14)
sysml9
pyspark8
petastorm8
pyarrow7
parquet7
algorithm7
pytorch6
deep-learning6
machine-learning6
tensorflow6
python6
distributed-training3
keras1
converter1
Programming languages (2)
Github contributions (5)
gueguenster/maxtree
Apr 2018 - May 2021
implements the maxtree algorithm with python binding
Contributions:1 release, 85 commits, 22 PRs in 3 years 1 month
python
gueguenster/petastorm
Dec 2020 - Aug 2024
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.
Contributions:4 pushes, 1 branch in 3 years 9 months
pythontrainingdeep-learning-modelstensorflowdata-science
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