Gaël Varoquaux

gael

varoquaux@normalesup dot

org

Blog | Front Page

text

pdf

Welcome, the navigation bar on the right should help you find what you are looking for.

Personnal information

On this website, you will find my travel log
My CV (updated December 2009)
A link to my partner's site, Emmanuelle Gouillart, physics researcher at Saint Gobain.

My current thoughts and some news can be found on my blog. It talks most often about scientific computing with Python, but you will also find personal and professional updates.

Physics

I hold a Ph.D. in Physics. Until 2008, I was doing research on developing quantum-based atom-optic metrology, in particular, using quantum gases for atom-interferometric intertial sensing. More on the physics page...

Brain imaging and modeling

My current research is on building quantitative statistical and descriptive models of brain activity through functional imaging.

I develop algorithms and models for extracting salient and reproducible features from functional MRI images without using a paradigm, such as in resting-state studies. I focus on group models opening the door to between-subject comparisons.

In addition, I am working on using graphical models to do inter-subject or inter-group comparison of connectivity structures.

Scientific computing

Software

I contribute to a number of scientific computing libraries in Python:

Mayavi: 3D plotting and scientific visualization in Python.
pyreport: litterate programming for scientific code in Python.
joblib meta-programming for lightweight pipelining of scientific jobs in Python.

Manifesto

This section reflects only my personal opinion.

Scientific research relies more and more on computing. However, most of the researchers are not software engineers, and as computing is becoming ubiquitous, the limiting factor becomes more and more the human factor [G. Wilson, 2006] [P. Norvig, 2009].

Note

To address the needs of computing accross scientific fields, I believe that we need a general-purpose, high-level, interactive, and highly-readable language and set of tools for scientific computing.

C does not answer my needs: does a molecular biologist know about pointers? Should she?
Matlab does not answer my needs either: scientific work with computers is not only about numerical computation. Have you tried writing an experiment-control software with Matlab? How about file management? Inserting the algorithms in a web server.

We need better teaching material, that sit at interfaces between software engineer, and general science. Most top notch tools and libraries are full of domain-specific jargon and conventions.

For reproducible science, we need the code to be readable and to reflect the corresponding scientific operation. We need it to be unit-tested to ensure its correctness.

Note

We need to start considering scientific libraries as end-result of our research with the same importance than articles [J. Buckheit and D. Donoho. 1995]. They need to convey a scientific message, to be understandable and refutable. New results should be reproducible via published code [CISE Jan. 2009]. As for established algorithms, scientific libraries with their documentation and examples should be the textbooks of tomorrow.