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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Computer vision research aims to identify overweight people from social media face photos

16/03/2017

Researchers from MIT and the Qatar Computing Research Institute have developed a novel new facility in the current rush of interest towards computer vision – an algorithm that can identify overweight...

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Algorithm can create a bridge between Clinton and Trump supporters

20/02/2017

A growing number of people have expressed their concern about high levels of polarization in society. For instance, the World Economic Forum's report on global risks lists the increasing societal ...

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The hero big data needs? Data Civilizer helps scientists conquer the clutter

29/01/2017

Big data is a big deal. With these huge data sets, analysts can gain unprecedented insight into the hidden patterns of fields like physics, healthcare, and finance. Collecting and analyzing this data...

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Upcoming Events

2017

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QCRI-MIT CSAIL Annual Research Project Review 2017

Download ICS File 27/03/2017 ,

The QCRI – MIT CSAIL Annual Research Project Review is open to the public on Monday, March 27, 2017, at the HBKU Research Complex Multipurpose Room. The annual meeting is a highlight of a ...

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Past Events

MLDAS 2017

(MLDAS 2017) Machine Learning and Data Analytics Symposium

Download ICS File 13/03/2017  - 14/03/2017 , Qatar National Convention Centre

Machine Learning and Data Analytics Symposium - MLDAS 2017 Building on the success of the three previous events , Boeing and QCRI will hold the Fourth Machine Learning and Data Analytics Symposium (...

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Women in Data Science

Download ICS File 03/02/2017 ,

Here's a great chance to learn about the latest data science-related research in multiple domains, as part of a global project. Qatar's WiDS event will be held here at the HBKU Research Complex on ...

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News Releases

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QCRI summer 2017 internship applications open

11/03/2017

The Qatar Computing Research Institute, part of Hamad bin Khalifa University, has announced that applications for its summer internship program have opened. The internships are being offered to ...

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Leading AI expert Patrick Winston to visit Qatar

05/03/2017

Patrick Winston, a Professor of Artificial Intelligence and Computer Science at Massachusetts Institute of Technology’s Computer Science and Artificial Intelligence Laboratory, is to visit Qatar to ...

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Boeing Partners with QCRI for fourth annual Machine Learning and Data Analytics Symposium (MLDAS)

09/02/2017

The Boeing Company has announced that it will once again partner with the Qatar Computing Research Institute (QCRI), part of Hamad bin Khalifa University, to host the fourth annual Machine Learning ...

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