قدِّم طلبك الآن 
ميشيل اوبتيت
عالم أول
ميشيل اوبتيت
عالم أول
المؤهلات العلمية
Accreditation for Research Supervision (HDR) in Computer Science
PhD in Industrial Engineering
الكيان
معهد قطر لبحوث الحوسبة
Divison
الحوسبة الاجتماعية
السيرة الذاتية
Dr. Michaël Aupetit works at QCRI since 2014. He is with the Social Computing group.
Before joining QCRI, Michaël worked for 10 years as a research scientist and senior expert in data mining and visual analytics at CEA LIST in Paris Saclay, where he designed decision support systems to solve complex industrial problems in health and security domains.
Michaël initiated and co-organized 5 international workshops. He has been PC member of IEEE VAST, PacificVis, ESANN, and ICANN conferences, and has reviewed hundreds of papers for top journals and conferences, has more than 70 publications, and holds 2 WO and 1 EP patents. He obtained the Habilitation for Research Supervision (HDR) in Computer Science from Paris 11 Orsay University in 2012, and the Ph. D degree in Industrial Engineering from Grenoble National Polytechnic Institute (INPG) in 2001.
Accreditation for Research Supervision (HDR) in Computer Science
Paris 11 Orsay University; Orsay/France
2012
PhD in Industrial Engineering
Grenoble National Polytechnic Institute (INPG); Grenoble/France
2001
MSc in Robotics and Microelectronics
Montpelier University, Montpellier, France
1998
Engineering in Computer Science specialized in Artificial Intelligence
Ecole pour les Etudes et la Recherche en Informatique et Electronique (EERIE); Nîmes/France
1998
Senior Scientist
Qatar Computing Research Institute; Hamad Bin Khalifa University
2019 - Present
Scientist
Qatar Computing Research Institute; Hamad Bin Khalifa University
2014 - 2018
Senior Expert Scientist
Laboratory for Integration of Systems and Technology; CEA Tech
2008 - 2014
Research Scientist
Department of Earth and Environmental Science; CEA DAM
2004 - 2008
Postdoc
Department of Earth and Environmental Science; CEA DAM
2002 - 2004
- Linking Techniques with Distortions, Tasks, and Layout Enrichment; IEEE Transactions on Visualization and Computer Graphics 2018; https://doi.org/10.1109/TVCG.2018.2846735
- KinVis: A visualization tool to detect cryptic relatedness in genetic datasets; Bioinformatics 2018; https://doi.org/10.1093/bioinformatics/bty1028
- Computer Graphics Forum 34(3):201-210, 2015; https://doi.org/10.1111/cgf.12632
- a supervised multidimensional scaling technique which preserves the topology of the classes; International Journal of Pattern Recognition and Artificial Intelligence 29(6), 2015; https://doi.org/10.1142/S0218001415510088
- Sanity check for class-coloring-based evaluation of dimension reduction techniques; BELIV 2014:134-141; https://doi.org/10.1145/2669557.2669578
- Sanity check and topological clues for linear and nonlinear mappings; Computer Graphics Forum 30(1):113–125, 2011; https://doi.org/10.1111/j.1467-8659.2010.01835.x
- Learning topology of a labeled data set with the supervised generative Gaussian graph; Neurocomputing 71(7-9):1283-1299, 2008; https://doi.org/10.1016/j.neucom.2007.12.028
- Concerning the differentiability of the energy function in vector quantization algorithms; Neural Networks 20:621-630, 2007; https://doi.org/10.1016/j.neunet.2006.11.006
- Learning Topology with the Generative Gaussian Graph and the EM algorithm; Advances in Neural Information Processing and Systems (NIPS) 18, 2006; https://papers.nips.cc/paper/2922-learning-topology-with-the-generative-gaussian-graph-and-the-em-algorithm
- How to help seismic analysts to verify the French seismic bulletin? ; Engineering Applications of Artificial Intelligence 19(7):797-806, 2006; https://doi.org/10.1016/j.engappai.2006.05.008
- High-dimensional labeled data analysis with topology representing graphs; Neurocomputing 63:139-169, 2005; https://doi.org/10.1016/j.neucom.2004.04.009
- gamma-Observable Neighbours for Vector Quantization; Neural Networks 15(8-9):1017-1027, 2002; https://doi.org/10.1016/S0893-6080(02)00076-X
- 2007; Award for the Best presentation at CAp 2007 French conf. on Mach.Learning; SPSS; France
- 1998; Best M.Sc internship; CEA; Nîmes/France