Thibaut Kulak

data scientist

Paris, France

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Thibaut en quelques mots

I am about to graduate from Ecole Centrale Paris and the MVA research master at ENS, I am specialized on Artificial Intelligence/Deep Learning, and am looking forward to start a PhD in AI.

I have much experience with Python and TensorFlow and can therefore help you for any data science task, including but ont only limited to the development of Deep Learning models. My substantial experience in Machine Learning skills me for advising in this field, I can therefore help you define the feasibility of a project relatively to the state of the art Artificial Intelligence models.

I worked in Safran Morpho on a Deep Learning research project on Head Pose Estimation. I am currently finishing my master thesis at the AI lab of SoftBank Robotics, whose goal is sensorimotor prediction in partially observable environments.

I also participated in a few Kaggle competitions and gained much experience in Machine Learning.

During my formation at Ecole Centrale Paris and ENS, I worked on several research projects in Machine Learning/Artificial Intelligence such as :
- 3D shape and pose estimation of a person given a single video (Computer Vision)
- Inverse Reinforcement Learning in board games (Reinforcement Learning, Graphs)
- Sudoku solving by convex relaxation (Optimization)
- Deep dreaming (Deep Learning)

I am passionate about Machine Learning and would love to work on an ambitious project, please don't hesitate to contact for any additional information or to discuss your project.

Expériences

octobre 2016 - mars 2017 | 92130 Issy-les-Moulineaux, France

Sécurité civile

Safran Morpho

Research Intern in Deep Learning

Included in my formation at Ecole Centrale Paris, I worked one day every week on a research project at Safran Morpho during my last year of studies. The research project was on Head Pose Estimation with Deep Learning methods. The bottleneck of this approach is that it requires lots of data, which is expensive to obtain, that's why I worked on using unlabeled images to improve the model.

The report of the project is available on :
https://www.dropbox.com/sh/ak0nzhnbdslgnbl/AACLE5sHASw4ULMqS-IbdVLfa?dl=0
avril 2017 - Aujourd'hui | Paris, France

Centres de recherche

Softbank Robotics

Research intern in AI/Deep Learning

When interacting with its environment, a robot must be able to predict the consequences of his actions. The goal of my internship in the AI Lab of Softbank Robotics is to use Recurrent Neural Networks to predict the future values of the robots's sensors given the robot's actual sensor values and its motor commands. I am working on how to learn latent variables from the environment to improve the prediction. Learning those latent variables is unsupervised, but I would like variables like position of the robot to emerge naturally, similarly to the rat's place cells for instance.

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