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International master in

Artificial Intelligence & advanced Visual Computing (AI-ViC)

Ecole Polytechnique

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

Link to the official page on the Ecole Polytechnique website.

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 Master curriculum (which opened in September 2018) strongly focuses on Artificial Intelligence, including statistical learning and applications to data science. It also covers the complementary field of 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 are 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 here) :

  • Deep learning
  • AI in Computer Graphics: from smart design tools to the animation of autonomous characters
  • Speech recognition, natural language processing and synthesis
  • Computer vision (images-based 3D reconstruction, recognition in images & videos)
  • Geometric data analysis and deep learning on such data
  • 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 page), while transverse projects will give some practical experience to each student in one or several domains of interest (see 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

  • Inria has been covering un 2018 and 2019 1 grant per year for 2 years, plus a PhD track in an Inria Team.
  • GOOGLE covered 2 grants per year for 3 years, plus a contribution to the related teaching and research.
  • ENEDIS covered 3 grants for students entering the program in 2018-2019, and is now covering 2 grants per year
  • IDEMIA is covering 1 grant per year since the beginning of the programm

We also recently welcomed young companies among our patners, all contributing as well to student grants.

  • Anatoscope is covering 1/2 grant per year for 2 years
  • Homiwoo is covering more than 1/2 grant per year for 2 years
  • InitML is covering 1/2 grant per year for 2 years
  • Gojob is covering more than 1/2 grant per year for 1 year

Internships and PhD proposals

Students are indeed welcome to fond their owns, but we gathered a few proposals here.

Contacts

The professors in charge are:

start.txt · Last modified: 2022/06/22 18:41 by cani