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Last update: September 2014

 

 

Michaël Aupetit

 

Qatar Computing Research Institute (http://qcri.org.qa/)   

Computational Science and Engineering

10th Floor, Tornado Tower,

PO Box 5825, Doha, Qatar

http://michael.aupetit.free.fr/

(+974) 445 47150 –  michael.aupetit@qf.org.qa

 

Key knowledge

Big Data

Machine Learning

Visual Analytics

Decision support

Algorithmic

Statistics

Computational geometry

Computational Topology

 

Matlab

Java

Map Reduce

D3js

Project management

Oral presentation

Business approach

Publications and patents

Current position (more)

 

2014 – today

Research Scientist in Computer Science

Qatar Computing Research Institute

Computational Science and Engineering

10th Floor, Tornado Tower,

PO Box 5825, Doha, Qatar

 http://qcri.org.qa/

 

Highest diploma (more)

 

2012

Habilitation for Research Supervision in Computer Science

Approches topologiques pour l’analyse exploratoire de données et l’aide à la décision

(Topological approaches for exploratory data analysis and decision support)

07/11/2012 – LRI, Paris Sud 11 University – Paris Saclay Campus, France

 

Current project (more)

 

 

 

2014 – today

Big Data Visual Analytics for cancer data analysis

D3js

Machine Learning

Topological inference

 

Publications & Patents (more)

1999 – today

International patents: 3 (+3)

International journals: 9 (+2)

International conferences: 18

International workshops: 4

International invited talks: 1

National journals: 5

National conferences: 14  

National workshops: 2

National invited talks: 3

 

 

 

Research summary (more)

My research focuses on designing new techniques to take up challenging scientific issues at the crossing of Computational Topology, Visual Analytics and Machine Learning, to support humans in their decision facing (big) data coming from the monitoring of (complex) systems.

I design intelligent user-centric decision support systems to make easier Human Machine Interaction. I open the black-box of Machine Learning techniques to allow human users to get access to the knowledge acquired by the machine, in order to get the best combination of machine’s speed and accuracy and human intelligence.

 

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