Christel VRAIN
Professor
LIFO - université of Orléans
BP 6759
45067 Orléans Cedex 2
France
Tel: 33 2 38 41 72 89
Fax: 33 2 38 41 71 37
email : Christel.Vrain at univ-orleans.fr
French version
Recent administrative charges
Main Teaching Activities
- Machine
Learning
- Data
Mining
- Logic,
Calculability
- Artificial
Intelligence
Research Activities
Keywords
- Machine Learning
- Inductive Logic Programming
- Knowledge Discovery in Databases
Recent Projects
- GD2GS:
From genomic data to graph structure (http://gd2gs.ibisc.univ-evry.fr/) (teams involved in
the project: IBISC, HEUDIASYC, CEA fonctional genomic department, LIFO),
2006-2008
- ACI Biotim (teams
involved in the project: IMEDIA and Atoll teams from INRIA, IRD, INRA,
CEDRIC, LIFO), 2004 - 2006
Current PhD Students
- Thang Dinh Quang, (co-directed with M. Exbrayat) Statistical Relational Learning
- Jacques Henri Sublemontier (co-directed with G. Cleuziou and L. Martin)
Multi-sources unsupervised clustering
- Julie Dubois, (co-directed with L. Morin-Allory - ICOA, Institut de Chimie Analytique et Organique) chemoinformatics
Member of International Program
Committees
- KDD 2010
(16th ACM SIGKDD International on Knowledge Discovery and Data Mining)
- ECML/PKDD10 ,
ECML/PKDD
09
(European Conference on Machine Learning),
ECML 08
- ACML
09 (1st Asian Conf. On Machine Learning, univ. Nanjing)
- ICML 07
(International Conference on Machine Learning)
- ICTAI 08, ICTAI 07 (International
Conference on Tools for Artificial Intelligence)
- ISMIS 09, ISMIS 08, ISMIS 06
(International Symposium on Methodologies for Intelligent Systems)
- ILP 2010, ILP 2009, ILP 2008,
ILP 2007, ILP 2006, ILP 2005, ILP 2004 (Inductive Logic Programming
conference)
- First International Workshop on Interesting Knowledge Mining (IKM 09), lié à ICDM 09
- workshop MCD 08
during ICDM 08
-
- Text Mining, Human
Language Technologies and Information Retrieval workshop (TMHLTIR Workshop
of EPIA 2005)
Current research domains
- Machine
Learning and Inductive Logic Programming
- Inductive
Logic Programming and Databases - application to Knowledge Discovery in
Databases
- Learning
Association and Characteristization Rules in Relational Databases
- Application
of Machine Learning to Text Mining
- Applications: Geographic Information Systems, chemoinformatics, ...