Arthur Ouaknine Email and Phone Number
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Arthur Ouaknine personal email
I am a postdoctoral researcher fellow at McGill University and Mila (Quebec Artificial Intelligence Institute), supervised by David Rolnick. My research projects are focused on multimodal and multitask deep learning applied to forest monitoring. I’m also a core team member of Climate Change AI leading the webinars team.I completed my Ph.D. in March 2022 in collaboration between Institut Polytechnique de Paris (Telecom Paris; Image, Data and Signal department) and Valeo.ai (international research center in artificial intelligence applied to autonomous driving). The aim of my work was to use and adapt deep neural network architectures for scene understanding using automotive radar data and multi-sensor fusion.For more information, please visit my personal webpage: https://arthurouaknine.github.io/
Rubisco Ai
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Co-Founder And CtoRubisco Ai Sep 2024 - PresentMontréal, Québec, CanadaOur mission is to develop a transparent, robust and scalable tool for impactful forest monitoring—bringing new insights to forest conservation and management through advanced AI.
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Researcher FellowMcgill University Sep 2022 - PresentMontréal, Québec, CanadaCollaboration between McGill University and Mila (Quebec Artificial Intelligence Insitute).Postdoctoral researcher fellow in deep learning applied to climate change and forest monitoring.In particular, we are exploring foundation models for remote sensing in multi-modal, multi-task and multi-scale contexts for forest monitoring worldwide. -
Core Team MemberClimate Change Ai Feb 2023 - Present- Volunteer in a non-profit organization disseminating knowledge at the intersection of climate change and artificial intelligence.- Lead of the webinars team.- Co-leading the organization of the ICLR 2024 workshop "Tackling Climate Change with Machine Learning"- Supervising the organization of the NeurIPS 2024 workshop "Tackling Climate Change with Machine Learning" -
Phd Student In Deep LearningValeo Jan 2019 - Mar 2022Région De Paris, FrancePhD prepared in collaboration between Telecom Paris (French engineering school) and valeo.ai (international research lab in autonomous driving).Under the supervision of P. Pérez (valeo.ai), F. Tupin (Telecom Paris) and A. Newson (Telecom Paris).Subject: ”Scene understanding using deep learning algorithms applied to radar data for autonomous driving”.Keywords: deep learning algorithms, signal processing, computer vision, Range-Angle-Doppler representation, semantic segmentation.Publications:Paper: Raw High-Definition Radar for Multi-Task LearningAuthors: Julien Rebut, Arthur Ouaknine, Waqas Malik, Patrick PérezConference: CVPR 2022Link: https://arxiv.org/abs/2112.10646Paper: Multi-View Radar Semantic SegmentationAuthors: Arthur Ouaknine, Alasdair Newson, Patrick Pérez, Florence Tupin, Julien RebutConference: ICCV 2021Link: https://arxiv.org/abs/2103.16214Paper: CARRADA Dataset: Camera and Automotive Radar with Range-Angle-Doppler AnnotationsAuthors: Arthur Ouaknine, Alasdair Newson, Julien Rebut, Florence Tupin, Patrick PérezConference: ICPR 2020Link: https://arxiv.org/abs/2005.01456 -
Research EngineerValeo Sep 2018 - Dec 2018Région De Paris, France
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Research EngineerFreelance Jun 2018 - Jul 2018Région De Paris, France- R&D Mission (with Faircast): Detection of 3D objects in an apartments using Deep Learning algorithms. - Publication: Review of Deep Learning Algorithms for Image Semantic Segmentation
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Computer Vision EngineerZyl Sep 2017 - Mar 2018Région De Paris, FranceApplication of Deep Learning methods for image analysis embedded on mobile. - State-of-the-art of image classication, object detection models and Deep Learning model reduction. - Object detection using YOLOv2 for real time inference embedded on mobile. - Memories detection using VSO, decision tree and transfer learning. - Model embedding on Android / iOS.Programming: Python (Tensorflow/TFlite, Keras, Caffe, CoreML, sklearn, ...)Integration: CircleCI, DockerPublication: - Review of Deep Learning Algorithms for Image Classification - Review of Deep Learning Algorithms for Object Detection - Deep Learning Model Compression for Image Analysis: Methods and Architectures -
Machine Learning Research CollaborationSafran Identity & Security (Aka Morpho) Oct 2016 - Jun 2017Title: "Facial points recognition using Deep Learning and Active Learning process"This project is a collaborative work between five students of Telecom ParisTech School and Morpho, a Safran subsidiary working on identity and security. Using pictures scaled on the head of persons, we use a Convolutional Neural Network (CNN) model to predict the five important points of a head (left and right corners of the mouth, left and right eyes, top of the nose).Since picture annotation is time-consuming and because there is a few number of labelled data, the main objective in this project is to detect which data might have a bigger impact on the training of a CNN.In this project, we produce experiences to quantify uncertainties of a convolutional neural network on its predictions. In this way, we have the possibility to target pictures which could potentially bring the most various information needed by our model in its training.Thus, applying an active learning process on an unlabelled database helps us to create a customized and optimized training set. This iterative approach provides better performances for a fixed number of training data than a random selection of data.Programming: Python (Tensorflow) -
Data Scientist InternRexel France Apr 2016 - Sep 2016Région De Paris, FranceWithin the Business Analytics division of Rexel France, I realized different projects to analyse the customer’s path and their multiple channel interactions in order to realize an in-depth study on behaviour. - Text Mining analysis of a satisfaction survey using SPSS Text Analytics software. - Data audit from big databases. - Creation of simple variables with time series, cross variables, customers segmentations and formatting them. - Creation of predictive attrition models (prevention of churn) using SPSS Modeler software. Different types of models were tested: Logistic Regression, SVM, Bayesian Networks … Deepening and improvement of the Neural Network finally chosen. - Performance tests: ROC curve, Lift curve, Profit curve - Commercial visits management study as an action channel against attrition phenomenon. Creation of visit elasticity for each type of client and introduction of an optimisation issue. -
Text Mining Analyst InternEnedis (Ex Erdf) May 2015 - Sep 2015Région De Paris, FranceWithin the new “Mission Numérique” division of ENEDIS (ex ERDF), I implemented Text Mining methods on incident reports of the medium-voltage grid of electricity in Paris, France. - Manipulation and formatting the unstructured incident reports. - Research and creation of programming tools to extract information in textual fields of these reports. - Design a programme enable to analyse and realize an automatic treatment of textual data using R software. - Document the functions, methods used for Text Mining and overall functioning of the treatment program - Creation of a database grouping indicators and aggregates created from the Text Mining analysis results with the objective of implementing a Logistic Regression model to predict incidents.
Arthur Ouaknine Skills
Arthur Ouaknine Education Details
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Deep Learning -
Post M.Sc. Degree, Big Data And Machine Learning -
With Honors -
With Honors
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Applied Mathematics
Frequently Asked Questions about Arthur Ouaknine
What company does Arthur Ouaknine work for?
Arthur Ouaknine works for Rubisco Ai
What is Arthur Ouaknine's role at the current company?
Arthur Ouaknine's current role is Researcher Fellow @McGill & Mila | Co-founder & CTO @Rubisco AI | Core member @Climate Change AI.
What is Arthur Ouaknine's email address?
Arthur Ouaknine's email address is ao****@****exel.fr
What schools did Arthur Ouaknine attend?
Arthur Ouaknine attended Institut Polytechnique De Paris, Télécom Paris, Université Paris 1 Panthéon-Sorbonne, Université Paris 1 Panthéon-Sorbonne, Université Denis Diderot (Paris Vii).
What are some of Arthur Ouaknine's interests?
Arthur Ouaknine has interest in Science And Technology, Environment.
What skills is Arthur Ouaknine known for?
Arthur Ouaknine has skills like Machine Learning, Data Science, Python, Data Analysis, Java, R, Hadoop, Spark, Mongodb, Sas, Sql, Vba.
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