Latest tweets

 

Latest posts

Of software and Science. Reproducible science: what, why, and how

At MLOSS 15 we brainstormed on reproducible science, discussing why we care about software in computer science. Here is a summary blending notes from the discussions with my opinion.

“Without engineering, science is not more than philosophy”    —   the community

How do we enable better Science? Why do we do software ...

Nilearn 0.2: more powerful machine learning for neuroimaging

After 6 months of efforts, We just released version 0.2 of nilearn, dedicated to making machine learning in neuroimaging easier and more powerful.

This release integrates the features of the july sprint, and more.

Highlights

Better documentation ...

Job offer: data crunching brain functional connectivity for biomarkers

My research group is looking to fill a post-doc position on learning biomarkers from functional connectivity.

Scientific context

The challenge is to use resting-state fMRI at the level of a population to understand how intrinsic functional connectivity captures pathologies and other cognitive phenotypes. Rest fMRI is a promising tool for ...

MLOSS 2015: wising up to building open-source machine learning

Note

The 2015 edition of the machine learning open source software (MLOSS) workshop was full of very mature discussions that I strive to report here.

I give links to the videos. Some machine-learning researchers have great thoughts about growing communities of coders, about code as a process and a deliverable ...

Nilearn sprint: hacking neuroimaging machine learning

A couple of weeks ago, we had in Paris the second international nilearn sprint, dedicated to making machine learning in neuroimaging easier and more powerful.

It was such a fantastic experience, as nilearn is really shaping up as a simple yet powerful tool, and there is a lot of enthusiasm ...

Software for reproducible science: let’s not have a misunderstanding

Note

tl;dr: Reproducibilty is a noble cause and scientific software a promising vessel. But excess of reproducibility can be at odds with the housekeeping required for good software engineering. Code that “just works” should not be taken for granted.

This post advocates for a progressive consolidation effort of scientific ...

MLOSS: machine learning open source software workshop @ ICML 2015

Note

This year again we will have an exciting workshop on the leading-edge machine-learning open-source software. This subject is central to many, because software is how we propagate, reuse, and apply progress in machine learning.

Want to present a project? The deadline for the call for papers is Apr 28th ...

Job offer: working on open source data processing in Python

We, Parietal team at INRIA, are recruiting software developers to work on open source machine learning and neuroimaging software in Python.

In general, we are looking for people who:

  • have a mathematical mindset,
  • are curious about data (ie like looking at data and understanding it)
  • have an affinity for problem-solving ...

Euroscipy 2015: Call for paper

EuroScipy 2015, the annual conference on Python in science will take place in Cambridge, UK on 26-30 August 2015. The conference features two days of tutorials followed by two days of scientific talks & posters and an extra day dedicated to developer sprints. It is the major event in Europe in ...

PRNI 2016: call for organization

The steering committee of PRNI (Pattern Recognition for NeuroImaging) is opening a call for bid to organize the conference in June 2016, in Europe