Education

PhD in Computer Graphics, Télécom Paris (Institut Polytechnique de Paris)

Programmable shape representations, supervised by Pr. Tamy Boubekeur.

M.A. Arts & Technologies de l'Image, Université Paris 8 (Paris)

Computer Graphics, Computer Arts, 3D Modeling, Rendering, Compositing, Game Engines, Animation, VFX

M.Sc. in Computer Science — M2 MVA, École normale supérieure de Cachan (Cachan)

Applied Mathematics, Machine Learning, Graphical Models, Reinforcement Learning, Computer Vision, Medical Imaging, Computational Photography, 3D Point Clouds

M.Sc. in Computer Science — M1 MPRI, École normale supérieure (Paris)

Category theory, Computer Vision, Machine learning, Robotics, Software engineering, Quantum Computing.

B.Sc. in Computer Science, École normale supérieure (Paris)

Algorithmics, Compilation, Formal languages, Lambda calculus, Hardware systems, Operating systems, Networks, Signal processing. Passed with Mention Très Bien (highest honors)

Classes Préparatoires aux Grandes Écoles (MPSI, MP*), Lycée Saint-Louis (Paris)

Admitted at the École normale supérieure in Mathematics, Physics and Computer Science, ranked 20 (out of 1480)

Scientific Baccalauréat, Lycée Les Pierres Vives (Carrières sur Seine)

With music minor, Passed with Mention Très Bien

Experiences

FX Artist, Mikros MPC, Paris, France

Procedural modeling and smoke effects using mainly Houdini for VFX in advertising

Research intern in Computer Graphics, Télécom ParisTech, Paris, France

Geometry-Material-Lighting synchronized models for multi-resolution real-time rendering, supervised by Pr. Tamy Boubekeur.

Pipeline TD, rise|fx, Berlin, Germany

Development of render farm manager and pipeline tools for visual effects artists.

Independent Contractor in Deep Learning R&D, Interactions, Tele-working

Assist with Deep Neural Networks optimization activities for Automatic Speech Recognition.
Development of a flexible experimentation setup.

Research intern in Deep Learning, Interactions, New York, US

Exploration of applications of Deep and Recurrent Neural Networks to Automatic Speech Recognition, supervised by Dr. Patrick Haffner.

Research intern in Computer Graphics, IMAGINE, Inria Grenoble, France

Procedural generation of terrain from simple vector map using plate tectonics and erosion simulation on GPU, supervised by Pr. Marie-Paule Cani.

Developer and designer of CitizenWatt, http://citizenwatt.paris

Electrical consumption sensor and easy-to-use data visualization interface, supported by Paris city hall.

Other Skills

Computer Programming

Python, C, C++, C#, Lua, OCaml, Java, MATLAB.
Various programming paradigms and software architecture.

Deep Learning

Neural Net architectures (DNN, RNN, CNN).
Deep Learning tools (Torch, Theano, TensorFlow).

Web technologies

HTML, CSS, JavaScript, NodeJS, PHP.

Languages

French (mother tongue), English (business level), German (ein bischen).

Music

Harpsichord (5 yrs), Guitar (2 yrs), Piano (2 yrs).
Studied solfège, and a bit of Music History.

Computer Graphics

Custom Engines

OpenGL
Shader programming
Path tracing
Raymarching
DirectX

Game Engines

Unity
Godot
BGE
Unreal

3D Modeling

Blender
Houdini
Maya
Substance

2D Graphics

Inkscape
GIMP
Photoshop
Illustrator

Rendering

Arnold
Cycles

Compositing

After Effets
Natron
Nuke

Interests

Internet and Indie Web

Self-hosted web services and linux server administration.

Hacking and electronics

Member of the ENS hack-lab, hackEns (http://hackens.org/)

Sociology

Especially related to digital worlds

Writing

Mostly fiction or pedagogical content

Photography

Pedagogy

Mountaineering

Climbing, Walking, Nature

Publications

Generation of Folded Terrains from Simple Vector Maps

Élie Michel, Arnaud Emilien, Marie-Paule Cani. In Eurographics. 2015. [PDF]

2015__Michel__Generation_of_Folded_Terrains_from_Simple_Vector_Maps.pdf

For more academic writing, see the Research page.