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==== Graduate Degree in ====
====== Artificial Intelligence & Advanced Visual Computing (AI-ViC)======

** Ecole Polytechnique ** 

//In collaboration with Inria, Ensta, Telecom Paris-Tech.//


==== Motivations ====

At the edge between computer science and applied mathematics, **Artificial Intelligence** (AI) is a
constantly growing field in which recent advances are truly impressive. Its goal is to create intellige nt
agents or systems capable of operating on their own to achieve difficult goals, such as decision-
making or creation tasks. This can be done using the modeling of knowledge and of reasoning
mechanisms and/or by relying on statistical learning (from Bayesian models to Deep Learning) where
the training data is either collected at once or on the fly. Besides developing these methods,
competitive research on their reliability is of primary interest.

Combined with **Visual Computing** techniques, a part of computer science that studies the processing
and simulation of visual information in all its forms (from images and videos to 3D virtual worlds),
Artificial Intelligence leads to strong societal impact applications, as for instance:

  * Searching the mass of online audio-visual contents, to process, edit or re-arrange them, leading to the creation of new interactive educational or cultural media;
  * Controlling drones or autonomous vehicles so that they move according to the surrounding dynamic environment and to some pre-specified rules;
  * Synthesizing virtual 3D characters for gaming, online retailing, serious games and 3D feature films, with behaviors matching to some extent those of real humans;
  * Designing, fabricating and controlling soft robots dedicated to various difficult tasks, from personal assistance to micro-surgery;
  * Using data analysis in high dimension and statistical learning to solve decision making problems in other domains such as finance, banking and insurance.

==== Objectives ====

This new Master curriculum (opening in September 2018) will strongly focus on Artific ia l
Intelligence, including statistical learning and applications to data science. It will also cover the
complementary field of advanced Visual Computing, including 3D computer graphics, virtual and
augmented reality, multimodal interaction, computer vision, robotics, and 3D Fabrication, which
either make use, or lead to the development of novel AI methods. This curriculum in Artificial
Intelligence and Visual Computing is therefore at the heart of digital sciences and of its most
promising, recent applications.

Courses will be given by Professors from Ecole Polytechnique and partner institutes and companies.
All courses will be held in English. Both French and foreign students are welcome.


==== Curriculum description  ==== 

The first 4 weeks will consist in crash courses in either mathematics (statistical analysis, introductio nto Machine Learning) or in Computer Science (C++ programming, basics of 3D modeling and algorithmic geometry), in order to complement the original training discipline of the student.

It will be followed by two training periods of 2.5 months, consisting of courses on the following
topics **(detailed version [[curriculum|here]])** :

  * Deep learning
  * Data analysis : geometry and topology in arbitrary dimensions
  * Speech recognition, natural language processing and synthesis
  * Advanced 3D graphics : smart geometry and visual simulation
  * Computer vision (images-based 3D reconstruction, recognition in images & videos)
 

  * Reinforcement learning
  * Robot motion planning, reachable sets, control of hybrid systems, verification, application to drones
  * Embodied conversational agents
  * Soft robots: simulation, fabrication, and control
  * Virtual and augmented reality, brain-computer interfaces and multi- modal interaction.

In complement, a weekly seminar will enable to discuss ethical issues and novel applications (**see [[seminar|seminar page]]**), while transverse projects will give some practical experience to each student in one or several domains of interest  (**see [[transverse|transverse projects page]]**).


The last part of the school year will consist in a six months research project, conducted either in a public or in a private research lab (among relevant companies, we suggest: Google, Facebook, Ubisoft, Dassault, Thales, etc).

==== Student Applications ====

We are looking for very strong students with an initial high quality training in either Computer Science or Applied Mathematics, since crash courses at the beginning of the curriculum can only be taken in one of these disciplines.

Selection will be based on a motivation letter, the CV of the candidate, their list of marks and rank in former degrees, and on two support letters from former professors and/or project supervisors having directly interacted with the student.

How to apply: details to come soon!

- Please, already drop us an email if you are interested, or if you have any question.


==== Industrial Partnership / Cercle des partenaires ====

Work in progress. 
  * GOOGLE is covering 2 grants per year for 3 years, plus a contribution to the related teaching and research.
  * ENEDIS is covering 3 grants for students entering the program in 2018-2019. 
  * Inria is corvering 1 grant per year for 3 years, plus a PhD track in an Inria Team.



==== Contacts ====

The professors in charge are:

  * [[https://www.lix.polytechnique.fr/stream/members/marie-paule-cani/|Marie-Paule Cani]], Computer Science (LIX / DIX), Ecole Polytechnique [[marie-paule.cani@polytechnique.edu]]

  * [[http://www.normalesup.org/~scornet/ | Erwan Scornet]], Applied Math (CMAP / DMAP), Ecole Polytechnique [[erwan.scornet@polytechnique.edu]]
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