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-====== Master of Science and Technology in Artificial Intelligence & Advanced Visual Computing (MScT in AI-ViC) ======
+====== Master of Science and Technology in Artificial Intelligence & advanced Visual Computing (MScT in AI-ViC) ======
 ** Ecole Polytechnique **
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 ==== Motivation ====
-In the intersection of Computer Science and Applied Mathematics, **Artificial Intelligence (AI)** is a steadily growing field generating a wealth of impressive achievements. The goal in AI is to learn and extrapolate from data. In recent years AI systems have been extended to process data in a variety of modalities including images, videos, text, point clouds and graphs, among others. This has led to growing societal impact and an ever-increasing academic and industrial interest. Current applications in AI range from text and/or video generation to drug design to name just a few. With the pervasive use of AI methods, also their reliability and robustness as well as ethical and legal considerations are of growing importance.
+In the intersection of Computer Science and Applied Mathematics, **Artificial Intelligence (AI)** is a steadily growing field generating a wealth of impressive achievements. The goal of AI is to develop intelligent systems able to help with complex tasks. This requires knowledge and reasoning, and in recent years also includes learning from data. The field of AI is currently progressing at a rapid speed. This has led to growing societal impact and an ever-increasing academic and industrial interest, even more so with the emergence of generative AI. Due to the pervasive use of AI methods, improving their reliability and robustness as well as accounting for their ethical and legal aspects have become mandatory.
-Combined with **Visual Computing (ViC)** 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:
+Combined with **Visual Computing (ViC)** techniques, a part of Computer Science that studies the processing and simulation of visual information in all its forms (from text, graphs, sound, images and videos to 3D virtual worlds), Artificial Intelligence leads to strong societal impact applications, such 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;
+  * Controlling drones, 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.
+  * Aiding in the interpretation of medical scans and enabling precision medicine by accelerating drug discovery.
 ==== Objectives ====
-This Master (which opened in September 2018) strongly focuses on Artificial Intelligence, including machine and deep learning. It also puts strong emphasis on 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 of, 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 some of its most promising, recent applications.
+This Master Program (which opened in September 2018) strongly focuses on Artificial Intelligence, including machine and deep learning. It also puts strong emphasis on 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 of, 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 some of its most promising, recent applications.
 Courses are given by professors from Ecole Polytechnique and partner institutes and companies.
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-==== Curriculum description  ====
+==== 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.
+The first week consists of refresher courses in mathematics (statistical analysis, introduction to Machine Learning) and Computer Science (C++ programming, basics of 3D modeling and algorithmic geometry), to complement the existing academic background of the students.
-It will be followed by two training periods of 2.5 months, consisting of courses on the following
+It will be followed by two training periods of 2.5 months, consisting of courses on the following topics **(detailed version [[https://msct.dix.polytechnique.fr/aivic/wiki/doku.php?id=curriculum|here]])** :
-topics **(detailed version [[curriculum|here]])** :
-  * Deep learning
+  * Deep Learning, Generative AI and Reinforcement 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
+  * AI in Computer Graphics, Virtual and Augmented Reality
+  * AI on sequence data including text (LLMs)
+  * Computer vision (images-based 3D reconstruction, recognition in images & videos)
+  * Robotics from motion planning to the design of soft robots for medical applications
-  * Reinforcement learning
+In complement, a weekly seminar will encourage discussions of ethical issues and novel applications, while transverse projects will give some practical, real-world experience to each student in one or several domains of interest.
-  * 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 [[seminarprogramm|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 of a five- to six-month research project, conducted either in a public or private research lab.
-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.
+We are looking for very strong students with initial high-quality training in either Computer Science or Applied Mathematics.
-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.
+Please take a look at the [[https://programmes.polytechnique.edu/en/master/admissions-msct/application-deadlines-procedure | official documentation]] for application process details.
-How to apply: details to come soon!
-- Please, already drop us an email if you are interested, or if you have any question.
+==== Industrial & Institutional Partnership / Cercle des partenaires ====
+Our MScT is accompanied by an active group of industrial and institutional partners contributing both student grants and transverse projects, as well as student internships. Some in the past, some currently, these partners include Inria, Google, Enedis, Idemia, Helsing as well as, younger companies such as Anatoscope, Homiwoo, InitML and Wemap.
-==== 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.
+==== Internships and PhD proposals ====
-  * 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
+Students have the option to either find their own internship position or to choose one of the internship proposals that we have made available **[[https://msct.dix.polytechnique.fr/aivic/wiki/doku.php?id=internships|here]]** and are regularly updating.
-  * 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 [[internships|here]].
 ==== Contacts ====
-The professors in charge are:
+The academic co-directors of the MScT are:
-  * Maks Ovskanikov, Computer Science (LIX / DIX), Ecole Polytechnique [[maks@lix.polytechnique.fr]]
+  * Marie Paule Cani, Computer Science (LIX / DIX), Ecole Polytechnique [[marie-paule.cani@polytechnique.edu]]
-  * Vicky Kalogeiton, Computer Science (LIX / DIX), Ecole Polytechnique [[vicky.kalogeiton@polytechnique.edu]]
+  * Johannes Lutzeyer, Computer Science (LIX / DIX), Ecole Polytechnique [[johannes.lutzeyer@polytechnique.edu]]
-  * Pierre Latouche, Applied Mathematics (DMAP / DepMap), Ecole Polytechnique [[pierre.latouche@polytechnique.edu]]
+  * Erwan Le Pennec, Applied Mathematics (DMAP / DepMap), Ecole Polytechnique [[erwan.le-pennec@polytechnique.edu]]
+  * Aymeric Dieuleveut, Applied Mathematics (DMAP / DepMap), Ecole Polytechnique [[aymeric.dieuleveut@polytechnique.edu]]
+Please don't hesitate to contact us!