Jean Barbier

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Mathematical physics of information processing systems

View the Project on GitHub jeanbarbier/jeanbarbier

Hello world

I’m Jean Barbier, a Research Scientist (Tenured Associate Professor) in mathematical physics of signals and learning at the International Center for Theoretical Physics (ICTP), a UNESCO institute. Our mission is not only the research excellence, but also teaching and scientific capacity building for the developing world: ICTP really is a special place to do top research and make a positive impact, worldwide.

As secondary affiliation I’m part of the Theoretical and Scientific Data Science group at SISSA.

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Both my institutes are located in Trieste, a gorgeous Italian city famous for its quality of life and known as the “city of science”. Among many others, an enjoyable feature of ICTP is its location: it is easy to go for a swim at lunch time :)

ICTP

My research interests are centered around information processing systems such as appearing in machine learning, communication and error-correction, signal processing or computer science. I often study these systems and associated algorithms using statistical physics –the language used to describe phase transitions–, its close cousin information theory, and random matrix theory. I try to precisely (and rigorously) quantify what is the optimal performance one can aim for when processing (big) data, as well as how close to optimality one can operate when using computationally efficient algorithms.

To contact me use jbarbier@ictp.it

You can find a short CV here.

All my articles can be found through my google scholar.

I am part of the editorial board of the transactions on machine learning research. Do not hesitate to send your papers there!

A “wide audience” video on physics and information processing systems on Youtube. In order to go further on the links between statistical physics and inference without having to read a full research paper, check this perspective article.

A conference I particularly enjoy to organize every year (together with an amazing team of friends) is Youth in High-Dimensions. It showcases excellent young researchers working on high-dimensional statistics in a broad sense.

For prospective students who would like to do a PhD under my supervision, please check regularly the openings in the PhD program in Theoretical and Scientific Data Science at SISSA or directly contact me.

Few quotes I find particularly relevant (the two last are wrongly attributed to Albert Einstein, yet I like them):

An expert is a person who has found out by his own painful experience all the mistakes that one can make in a very narrow field. – Niels Bohr quoted by Eward Teller in LIFE magazine (6 September 1954).

Physics is like sex: sure, it may give some practical results, but that’s not why we do it. – Richard Feynman

If you can’t explain it simply, you don’t understand it well enough. – Probably based on a similar quote about explaining physics to a barmaid by Ernest Rutherford

Everything should be made as simple as possible, but not simpler. – The (long) story of that quote can be found here

In addition to science, I also enjoy a lot electronic music (some musical experiments from my previous life), and pretty much any mean of riding/gliding snow, water or air. I also love holding my breath while free diving.

ERC project CHORAL: Computational Hardness Of RepresentAtion Learning

I feel honoured to be a recipient of a Starting Grant in mathematics from the European Research Council.

CHORAL will develop novel statistical tools to better quantify the performance of neural networks trained from structured data. It will combine random matrix theory, statistical mechanics and information theory, and will blend physics together with mathematically rigorous approaches. Neural nets are amazingly powerful machines, but their theoretical understanding remains limited when compared to their evergrowing applications in science and technology. A related problem of fundamental interest to machine learning that the project will focus on is of “dictionary learning”.

See our recent preprint to get a sense of CHORAL’s starting point. See also a short article about the project.

If you are a motivated researcher looking for a postdoc position, do not hesitate to contact me (there will be openings soon). The ideal candidate has a background in at least one or two of the following disciplines:

As part of the ICTP community, the postdoc eager to help will also have many opportunities for capacity building in developing countries (but not only) through organization of events, travels and networking, teaching etc.

It is also a great moment to join the Trieste (data) science community thanks to the newly created Data Science & Artificial Intelligence Institute, see also here.

PhD positions on the project are available too and are funded through the PhD program in Theoretical and Scientific Data Science at SISSA (or contact me directly to discuss other opportunities).

Feel free to drop me a mail me to know more about the project and do not hesitate to spread the word :)

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