lehoaian

 

Adresse postale: 

 
LITA - UFR MIM, Université de Lorraine,
Ile du Saulcy, 57045 Metz Cedex 01, France            
Tel: (33) - [0] 3 - 87 31 54 41
Fax: (33) - [0] 3 - 87 31 53 09
Email: hoai-an.le-thi@univ-lorraine dot fr 

   

   Le Thi Hoai An
    Professeur des Universités Classe Exceptionnelle
    Directrice du Laboratoire d'Informatique Théorique et Appliquée   LITA
    Université de Lorraine.

 

 

 

 

 

 

 

 


 

  • Ancienne Élève de l'Ecole Normale Supérieure de Hanoi, Viet Nam (1976-1980).
  • Doctorat: Université de Rouen, France (Octobre 1992 - Décembre 1994).
  • Habilitation à Diriger des Recherches: Université de Rouen, France (Juin 1997).

 

 


 

 

   

  1982 - 1991: Enseignante-chercheuse  à l'ENS de Hanoi.

 

  1994 - 1997: Chercheuse à l'INSA-Rouen.

 

  1998 - 2003: Maître de Conférences à l'INSA-Rouen.

 

  2003 - 2008: Professeur 2e classe à l'université de Paul Verlaine - Metz.

 

  2008 - 2012: Professeur 1e classe à l'université de Paul Verlaine - Metz.

 

  Depuis 2012: Professeur Classe Exceptionnelle à l'université de Lorraine. 


Le Thi Hoai An
 earned her PhD with Highest Distinction in Optimization in 1994, and her Habilitation in 1997 both from university of Rouen, France. From 1998 to 2003 she was Associate Professor at the National Institute for Applied Sciences, Rouen. Since 2003 she is Full Professor at the University of Paul Verlaine – Metz (which becomes University of Lorraine in 2012). She is currently Director of Laboratory of Theoretical & Applied Computer Science, university of Lorraine and serving as Exceptional Class Professor. She is the author/co-author of more than 200 journal articles, international conference papers and book chapters, the co-editor of 7 books and 12 special issues of international journals, and supervisor of 30 PhD theses. She is Chair of Scientific Committee and Chair of Organizing Committee as well as member of Scientific Committee of numerous International Conferences, and leader of several regional/national/international projects. Her research interests include Numerical Analysis, Optimization and Operations Research and their applications in Information Systems and Industrial Complex Systems in various fields such as, Data Mining and Machine Learning, Telecommunication, Transportation, Supply Chain and Management, Finance, Bioinformatics, Image Analysis, Cryptology, Security & Reliability. She is the co-founder (with Pham Dinh Tao) of DC programming and DCA, an innovative approach in nonconvex programming and global optimization. These theoretical and algorithmic tools, becoming now classic and increasingly popular, have been successfully applied by researchers and practitioners all the world over to model and solve their real-world smooth/nonsmooth nonconvex programs, especially in the large-scale setting.

 

 


 

    Événement 

   

      6th World Congress on Global Optimization WCGO 2019, July 8-10, 2019, Metz, France

https://wcgo2019.event.univ-lorraine.fr/

 

 

            Howard Rosenbrock Prize 2017

https://link.springer.com/article/10.1007/s11081-018-9397-2

This prize is awarded annually to honor the authors of the best paper published in Optimization and Engineering journal in the previous year. 

The winners of the 2017 Rosenbrock Prize are Hoai An Le Thi and Tao Pham Dinh for their work titled, Difference of convex functions algorithms (DCA) for image restoration via a Markov random field model.

 

 

30th birthday of DC programming and DCA, May 2015

http://www.lita.univ-lorraine.fr/iccsama2015/  

https://link.springer.com/article/10.1007/s10107-018-1235-y

 

 


 
   Publications
 récentes 

 

 

  • Convergence Analysis of Difference-of-Convex Algorithm with Subanalytic Data. Journal of Optimization Theory and Applications, Volume 179, Issue 1, pp. 103–126, October 2018
  • Accelerated Difference of Convex functions Algorithm and its Application to Sparse Binary Logistic Regression. IJCAI 2018, Proceedings of the 27th International Joint Conference on Artificial Intelligence, pp. 1369-1375, 2018
  • DC programming and DCA: thirty years of developments. Mathematical Programming, Volume 169, Issue 1, pp. 5-68, May 2018
  • An efficient DCA based algorithm for power control in large scale wireless networks. Applied Mathematics and Computation, Volume 318, pp. 215-226, 1 February 2018
  • Stochastic DCA for the Large-sum of Non-convex Functions Problem and its Application to Group Variable Selection in Classification. ICML 2017, Proceedings of the 34th International Conference on Machine Learning, pp. 3394-3403, 2017
  • Sparse Covariance Matrix Estimation by DCA-Based Algorithms. Neural Computation, Volume 29, Issue 11, pp. 3040-3077, November 2017
  • Difference of convex functions algorithms (DCA) for image restoration via a Markov random field model. Optimization and Engineering, Volume 18, Issue 4, pp. 873–906, December 2017
  • DC programming and DCA for enhancing Physical Layer Security via Cooperative Jamming, Computers and Operation ResearchVolume 87, pp. 235-244, November 2017
  • DC programming and DCA for solving Brugnano–Casulli piecewise linear systemsComputers and Operation Research, Volume 87, pp. 196-204, November 2017
 

 

      De plus ...