Florent Forest
Specialist Data Science & AI Engineering
Lausanne, Vaud, Switzerland
Summary
👤
Senior🎓
Top SchoolFlorent Forest is a Specialist in Data Science and AI Engineering with nine years of experience bridging academic research and industrial deployment, now based at Nestlé Research in Lausanne. He holds a PhD in Computer Science and a strong aerospace background (ISAE-SUPAERO, TU Berlin), which informs his focus on robust, interpretable and data-efficient deep learning for industrial use cases like predictive maintenance, visual inspection and signal processing. His research at EPFL concentrated on explainable AI and domain adaptation while his industry roles have emphasized MLOps, embedded vision optimization and scaling ML for fleet health monitoring. He combines hands-on skills across cloud-native pipelines, embedded deployment and full-stack tooling with academic rigor in publishing and teaching. Notably, he has repeatedly moved research prototypes into production—from microscope image analysis in a biotech startup to embedded vision on constrained devices—demonstrating both scientific depth and practical delivery.
9 years of coding experience
8 years of employment as a software developer
Preparatory school in theoretical Mathematics, Physics and Computer Science, Preparatory school in theoretical Mathematics, Physics and Computer Science at Lycée Janson-de-SaillyBaccalauréat S mathematics, Baccalauréat S mathematics at Lycée Marie LaurencinPh. D. Computer Science, Ph. D. Computer Science at Université Sorbonne Paris NordAeronautical and Astronautical Engineering, Aeronautical and Astronautical Engineering at Technische Universität BerlinMaster of Engineering Space Engineering, Data Science, Master of Engineering Space Engineering, Data Science at ISAE-SUPAERO
French, German, English, Spanish, Chinese
Stackoverflow
101reputation
41kreached
5answers
2questions
Github Skills (106)
python10
deep-learning10
clustering10
spark-ml10
representation-learning10
autoencoder10
ml10
neural-network10
trend10
tensorflow10
self-organizing-map10
machine-learning10
keras10
som10
deep-neural-networks10
Programming languages (7)
Github contributions (5)
FlorentF9/sparkml-som
Feb 2019 - Feb 2022
:sparkles: Spark ML implementation of SOM algorithm (Kohonen self-organizing map)
Contributions:16 commits, 8 pushes, 1 comment in 3 years
self-organizing-mapspark-mlsparkspark-mllibclustering
FlorentF9/DESOM
Jan 2019 - Jan 2020
:globe_with_meridians: Deep Embedded Self-Organizing Map: Joint Representation Learning and Self-Organization
Contributions:21 commits, 3 PRs, 20 pushes in 1 year
representation-learningself-organizing-mapclusteringdeep-learningautoencoder
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