À propos de Julien
I have been working almost 3 years at Tinyclues, as a R&D data scientist (Recommender systems).
I have also worked in a cardio-imagery start-up developing deep learning solutions for diagnostics, at Collège de France (Paris) in the mathematical neurosciences team, and in a Californian Start-up developing computer vision solutions for agriculture.
I graduated from Ecole Polytechnique and National University of Singapore, in Data Science.
Specialized in Deep learning and Bayesian modelling, I have also had the chance to work on a very wide range of subjects: Natural Language Processing, Computer vision, Time Series Prediction, Audio Analysis, Biotechnologies, Data Mining, ...
Espagnol
Capacité professionnelle limitée
Anglais
Capacité professionnelle complète
Français
Bilingue ou natif
Accepte de travailler sur site
Paris (jusqu’à 50 km)
Expériences
- TinycluesR&D Data ScientistHIGH TECHoctobre 2019 - avril 2022 (2 ans et 6 mois)Paris, FranceWorked on improving predictive model (recommender system), as well as the data stack.
- Institut Mutualiste MontsourisData ScientistBIOTECHNOLOGIESmai 2019 - octobre 2019 (5 mois)Paris, FranceI worked on the segmentation and classification of heart scanner images using deep learning. The idea was to evaluate the degree of stenosis of arteries, and generate a health check for each patient.
- Collège de FranceResearch InternshipCENTRES DE RECHERCHEavril 2017 - juillet 2018 (1 an et 3 mois)Paris, FranceI worked on the characterization of the maps of direction of the primary visual cortex in the Neuroscience department of Collège de France.
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Formations
- Master of Computer ScienceEcole Polytechnique2019Elective courses: - Applied Mathematics: Stochastic Processes, Dynamic Models, Optimization under Constraints, ... - Computer Science: Machine Learning Theory, NLP, Computer Vision, Big Data & Database Management, ... - Pure Mathematics: Differential Equations, Real and Complex Analysis, Galois' Theory... Long Term Projects: - Deep content based music genre classification (Signal Processing, Deep Learning) - "Can a robot conceptualize a music note ?" (Non supervised learning)
- Master of Computer Science (Specialization)National University of Singapore2019- Advanced Deep Learning: MLPs, CNNs, RNNs, GNNs, Attention models, Active learning... - Advanced NLP: Question answering, Sentiment analysis, seq-2-seq, Text classification, POS-Tagging, Dependency parsing... - Computer Vision: Image classification, Image processing, Video tracking, Image stitching,... - Uncertainty Modelling: Gaussian processes, Directed and Undirected graph models, Mixture models, Sampling, Variational inference... - Randomized Algorithms Analysis - Master's Thesis on Active Learning for Bayesian Recurrent Neural Networks