UMR CNRS 7253

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en:start [2019/02/25 17:23] – [Brief presentation] quostbenen:start [2024/01/22 11:31] (current) quostben
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-{{fr:benjamin_quost.jpg?175 |Benjamin Quost }} +{{fr:benjamin_quost.jpg?185 |Benjamin Quost }} 
 **Benjamin Quost** --- Associate professor with habilitation \\  **Benjamin Quost** --- Associate professor with habilitation \\ 
-Royallieu Research Center \\  +Royallieu research center, dept. Computer Science \\  
-Department of Computer Science \\  +Pascal building, office 201 \\ 
-building C, office C119 \\ +
 tel. : +33 (0)3 44 23 49 68 \\  tel. : +33 (0)3 44 23 49 68 \\ 
 fax : +33 (0)3 44 23 44 77 \\  fax : +33 (0)3 44 23 44 77 \\ 
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 [[http://www.utc.fr|Université de Technologie de Compiègne]] \\  [[http://www.utc.fr|Université de Technologie de Compiègne]] \\ 
 +Rue Roger Couttolenc, 60200 Compiègne 
 +
 [[http://www.hds.utc.fr|Laboratoire Heudiasyc]], UMR UTC-CNRS 7253 \\  [[http://www.hds.utc.fr|Laboratoire Heudiasyc]], UMR UTC-CNRS 7253 \\ 
-Rue Roger Couttolenc \\  +57 Av. de Landshut, 60200 Compiègne 
-CS 60319 \\  +
-60203 COMPIEGNE CEDEX +
  
 \\  \\ 
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 You will find here a summary of my professional activities. \\  You will find here a summary of my professional activities. \\ 
 For any other information, do not hesitate to contact me !  For any other information, do not hesitate to contact me ! 
- + 
- +
  
  
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 ====== Brief presentation ====== ====== Brief presentation ======
  
-I am now associate professor at the university of Technology of Compiègne. I have been the head of the [[https://moodle.utc.fr/course/view.php?id=1843|Data mining and Decision Making]] curriculum from January 2012 to February 2019+I am now associate professor (habil.) at the Université de Technologie de Compiègne. 
  
-My research focuses on machine learning, and more particularly supervised and unsupervised classification, from imperfect (imprecise, uncertain) information. I also work on classifier combination and data fusion issues. +My research focuses on machine learning, and more particularly on learning cautious models from scarce or poor data (Safe AIor under fairness constraints; on explainability, and in particular explaining indeterminate predictions; and on decision-making from partial information. I also work on classifier combination and data fusion issues. 
  
-I am interested in the theoretical framework of belief functions (also known as Dempster-Shafer theory) for representing and managing imprecision and uncertainty. +I am interested in the theoretical frameworks of probability theory, belief functions (also known as Dempster-Shafer theory), and imprecise probability, for representing and managing imprecision and uncertainty. 
  

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