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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Can AI Put An End To Fake News? Don't Be So Sure

07/10/2018

Fake news was the Collin’s word of the year for 2017 with good reason. In a year where politics-as-usual was torn apart at the seams, high-profile scandals rocked our faith in humanity and the ...

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MIT/QCRI system uses machine learning to build road maps

22/04/2018

Map apps may have changed our world, but they still haven’t mapped all of it yet. Specifically, mapping roads can be difficult and tedious: even after taking aerial images, companies still have to ...

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Improving disaster response efforts through data

08/02/2018

Extreme weather events put the most vulnerable communities at high risk. How can data analytics strengthen early warning systems and and support relief efforts for communities in need? The size and ...

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Upcoming Events

Past Events

2018

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QCRI Summer Internship Program

Download ICS File 06/05/2018  - 05/07/2018 , Hamad Bin Khalifa Research Complex

Each year, Qatar Computing Research Institute organizes a summer internship program for undergraduate students studying computer science, computer engineering and other disciplines. The internship is unpaid, and QCRI does not provide any visa support.

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Public Talk by Prof. Regina Barzilay "Artificial Intelligence for Oncology: Learning to Cure Cancer from Images and Text"

Download ICS File 27/03/2018 ,

Artificial Intelligence for Oncology: Learning to Cure Cancer from Images and Text A talk by Professor Regina Barzilay, MIT CSAIL Winner of 2017 MacArthur ‘genius grant’ At Education City Student ...

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QCRI & MIT-CSAIL Annual Project Review 2018

Download ICS File 27/03/2018 ,

Executive Overview Sessions Open to public Date:    Tuesday, March 27, 2018 Time:    9:00AM – 3:00PM Venue:  HBKU Research Complex Multipurpose Room To view full agenda, please click here . To RSVP, ...

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News Releases

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QCRI to offer kids’ computing activities at this year’s Darb Al Saai

03/12/2018

Tech fun and robotics computing activities will be available to children attending the annual family celebration from December 12 to 20.

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Global experts in artificial intelligence for transportation to visit Qatar for TASMU-QCAI workshop

18/11/2018

Urban computing experts from Europe, the US and Qatar are to discuss state-of-the-art advances in artificial intelligence for transportation with local stakeholders.

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QCAI to Conduct Joint Machine Learning School with BigML

16/10/2018

Two-day crash course to provide hands-on introduction to machine learning for industry practitioners, developers, graduate students and undergraduates.

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