Dr. Michael Aupetit

Scientist
Social Computing
QCRI offers the opportunity to advance the state-of-the-art in computational science, staying connected to real applications with great potential impact. Working at QCRI within an international team of passionate and inspiring researchers to explore ground-breaking ideas is really challenging and exciting.

Research Focus at QCRI

At QCRI, Michaël's research focuses on the use and usability of machine learning, topological inference and information visualization to bridge the gap between data complexity and analysts understanding in bioinformatics. He is also interested in distributed computing techniques to tackle scalability issues.

Previous Experience

Before joining QCRI, Michaël was a research scientist and senior expert in data mining and visual analytics at CEA LIST in Paris, where he designed cutting-edge algorithms and decision support systems to solve complex industrial problems in health and security domains.  Additionally, Michaël contributes to the Data Visualization and Data Analysis task force of the IEEE Computational Intelligence Society Technical Committee on Data Mining. He advised 5 PhD, 4 Post Doc, 2 engineers, and 16 interns. He also initiated and co-organized 3 international workshops. He has reviewed hundreds of papers for journals and conferences, has more than 60 publications, and holds 2 WO and 1 EP patent.

Professional Experience

  • Engineer and Research Scientist in Computer Science, CEA LIST, LADIS (Data Analysis and Intelligent Systems Laboratory), France - 2008 - 2014
  • Engineer and Research Scientist in Computer Science, CEA DAM (Detection and Geophysics Laboratory), France - 2004 - 2008
  • Post doctoral fellow in Computer Science, CEA DAM (Detection and Geophysics Laboratory), France, 2002 - 2004

Professional Associations and Awards

Associations
  • Data Visualization and Data Analytics task force of IEEE
  • French Association for Artificial Intelligence (AFAI)
  • French Stastical Society (SFdS)

Awards
  • SPSS Best Presentation Award at CAp 2007
Patents granted
  • Method and system for evaluating the class of test data in a large-dimension data space.  2010.  WO/2011/047889
  • Method and system for evaluating the resemblance of a query object to reference objects. 2010.  WO/2011/048219
  • Semi-supervised learning method system for data classification according to discriminating parameters. 2009. EP2180436A1

Education

  • Habilitation for Research Supervision (HDR) in Computer Science, Paris-Sud University - 2012
  • Ph. D in Industrial Engineering, Grenoble National Polytechnic Institute, France - 2001
  • MSc in Robotics and Microelectronics, Montpelier University, France - 1998
  • Computer Science Engineer specialized in Artifical Intelligence, Ecole pour les Etudes et la Recherche en Informatique et Electronique (EERIE), France - 1998


Selected Research

  • Sylvain Lespinats, Michaël Aupetit.  ClassiMap: a supervised multidimensional scaling technique which preserves the topology of the classes.  Submitted to Neurocomputing, Elsevier, 2014
  • Michaël Aupetit, Sanity Check for Class-coloring-based Evaluation of Dimension Reduction techniques. Workshop BELIV @ IEEE VIS 2014, Paris, November 2014
  • Michaël Aupetit, Nicolas Heulot, Jean-Daniel Fekete, A multidimensional brush for scatterplot data analytics. Poster @ IEEE VIS 2014, Paris, November 2014
  • Ricardo de Aldama, Michaël Aupetit, Interpretability in Fuzzy Systems Optimization: A Topological Approach. 15th Int. Conf. on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2014), Montpellier, July 2014
  • Sylvain Lespinats, Michaël Aupetit. ClassiMap : a Supervised Mapping Technique for Decision Support.  Workshop on Visual analytics using Multidimensional @ EuroVis 2013. Leipzig, Germany,  June 2013
  • Nicolas Heulot, Michaël Aupetit, Jean-Daniel Fekete. ProxiLens: Interactive Exploration of High-Dimensional Data using Projections. Workshop on Visual analytics using Multidimensional @ EuroVis 2013. Leipzig, Germany,  June 2013
  • Maxime Maillot, Michael Aupetit and Gerard Govaert. The Generative Simplicial Complex to extract Betti numbers from unlabeled data. Workshop on Algebraic Topology and Machine Learning @ NIPS2012, Lake Tahoe, NV, USA, December 2012
  • Nicolas Heulot, Michaël Aupetit, Jean-Daniel Fekete. ProxiViz: an Interactive Visualization Technique to Overcome Multidimensional Scaling Artifacts. Poster @ IEEE VIS 2012, Seattle, WA, USA, October 2012
  • Maxime Maillot, Michaël Aupetit, Gérard Govaert. A generative model that learns Betti numbers from a data set. ESANN’12 conference, Bruges, Belgium.  April 2012
  • Sylvain Lespinats, Michaël Aupetit. CheckViz : sanity check and topological clues for linear and nonlinear mappings (fast track EuroVis 2010) Computer Graphics Forum journal, 30(1): 113–125, Eurographics, July 2011
  • Michaël Aupetit. Nearly homogeneous multi-partitioning with a deterministic generator. Neurocomputing, 72(7-9): 1379-1389, Elsevier, March 2009
  • Gaillard Pierre, Michaël Aupetit, Gérard Govaert, Learning topology of a labeled data set with the supervised generative Gaussian graph. Neurocomputing, 71(7-9): 1283-1299, Elsevier, March 2008

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In the Media

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Improving disaster response efforts through data

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Upcoming Events

Past Events

2018

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QCRI's Creative Space to hold free app inventor workshop

Download ICS File 01/02/2018 ,

QCRI is to offer an introduction to mobile app development workshop for boys and girls aged 13-16. Students will learn the basics of mobile app development using the App Inventor platform. The ...

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2017

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QCRI's Creative Space launches free after-school computing courses for teenagers

Download ICS File 01/11/2017  - 20/12/2017 ,

We offer an App Inventor Course in Arabic for students aged 13-15 and an Arduino Programming Course in English for students aged 14-18. Courses are free. Please register quickly as places are limited.

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QCRI conducts first summer computing camps for kids

Download ICS File 16/07/2017  - 27/07/2017 ,

Children and teenagers have been given a rare chance to develop their computing skills with world-class computing scientists at the first summer computing camp conducted by the Qatar Computing ...

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News Releases

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QCRI scientists develop algorithm to detect brain cancer markers

30/01/2018

Scientists from the Qatar Computing Research Institute have developed a new algorithm that can identify driver genes of several types of gliomas, the most common and aggressive forms of primary brain...

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Research by QCRI's Jim Jansen among most influential of decade: top journals

13/12/2017

QCRI Social Computing group's principal scientist achieves rare honor.

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#Halal now a lifestyle definition on Instagram

29/11/2017

The word “halal” is no longer being defined only in a religious context but is becoming a lifestyle term associated with health and fashion around the globe, a new study of Instagram posts led by ...

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