Louis Wehenkel

Welcome to
Louis Wehenkel's home page


Cours (in French)


Affiliations at the University of Liège:



Systems and Modeling @ Montefiore
Systems Biology and Chemical Biology @ GIGA-R
Bioinformatics and Modeling @ GIGA-R

About me (briefly):

I am a former research associate of the Belgian National Fund for Scientific Research (F.N.R.S.) and presently professor of stochastic methods in the
Department of Electrical Engineering and Computer Science, at the University of Liège.

I do research in machine learning, stochastic simulation, and optimization, with applications in electric power systems, industrial process control, bioinformatics and computational systems biology. I am teaching courses on information theory and coding, stochastic processes, machine learning and data mining.

Since a few years, I have been strongly involved in the bioinformatics and systems biology research of the GIGA-R centre of the University of Liège (Systems Biology and Chemical Biology @ GIGA-R, Bioinformatics and Modeling @ GIGA-R, Alma-in-Silico project @ GIGA-R).
To reach me :
Mail : University of Liège - Institut Montefiore, Sart-Tilman B28, B-4000 Liège, Belgium.

Phone : Int+ 324 366 2684

Fax : Int+ 324 366 2984

Email : L.Wehenkel@ulg.ac.be

My research interests :

Back to top of this page Automatic learning, in particular tree based models, graphical models, reinforcement learning, with a focus on complex and large scale systems analysis and control,

Bioinformatics and computational systems biology, in particular biological systems and structures modeling, exploitation of proteomics, genomics, clinical and biomedical imaging data

Electric power transmission, generation and distribution systems, security and risk assessment, sequential decision making, optimization and long-term planning

Development of methods and applications of automatic learning, in particular in data mining, image and time-series classification, as well as for optimization

Cours (partly in French) :

Back to top of this page Eléments du calcul des probabilités (ULg : transparents et informations)

Eléments de statistique (ULg : transparents et informations)

Théorie de l'information et du codage: (ULg : transparents et informations)

Apprentissage inductif appliqué: (ULg : transparents et informations)

Introduction à l'apprentissage statistique: (ULg : transparents et informations)

Introduction aux processus stochastiques: (ULg : transparents et informations)

Bioinformatique: (ULg : transparents et informations)

Publications :

Back to top of this page Book : Automatic Learning Techniques in power systems, Kluwer Academic, 1998.

Papers : follow the link for more information.

Presentations : links to hardcopies (slides or handouts) of selected and/or recent presentations

Back to top of this page
NRC 2015: How to combine observational data sources with first principles of physics to build stable and transportable models for power system design and control? Plenary presentation at "Analytic Research Foundations for the Next-Generation Grid". A workshop of the National Research Council of the National Academies, Irvine Feb. 11-12, 2015 (10.2 Mbytes)

PSCC 2014: Adavanced optimization for power systems, Plenary survey presentation at 18th PSCC - Wroclaw, August 20, 2014 (4.6 Mbytes)

LRI-Orsay-2011 : Regression tree ensembles in the perspective of kernel-based methods, Laboratoire de Recherche en Informatique - Paris 11 - Orsay, Avril 23, 2011 (1.9 Mbytes)

MPI-Tuebingen-2009 : Regression tree ensembles in the perspective of kernel-based methods, Max Planck Insitute for Biological Cybernetics - Tuebingen, October 30, 2009 (1.9 Mbytes)

IAP V Study day 05 : Decision and regression tree ensemble methods and their applications in automatic learning, IAP V Study day, Colonster, May 19, 2005 (2563581 bytes)

ORBEL05 : Decision and regression tree ensemble methods and their applications in automatic learning, ORBEL Symposium on data mining, Brussels, March 16, 2005 (2596449 bytes)

EC-ICT05 : Closure of session 3, The future of ICT for power systems: emerging security challenges, European Commission, Brussels, February 3-4, 2005 (441856 bytes).

IREP2004 : Whither dynamic congestion management?, IREP Workshop, Contrina d'Ampezzo, August 2004. (98816 bytes)

CBRN2001 : Recent developments in tree induction for KDD. «Towards soft tree induction», Brasilian conference on Neural Networks, Rio, April 2001. (1592832 bytes)

PICA99 : Automatic learning and data mining applied to security assessment, PICA99 panel session, Santa Clara (Ca), May 1999, slides powerpoint gzipped (765770 bytes).

IBM-ARC 99 and IFSA97: Discretization of continuous attributes for supervised learning. Variance evaluation and variance reduction, May 1999, slides pdf (135148 bytes).

IBM-ARC 99 and IPMU92 : A global tree quality measure and its use for pruning, May 1999, slides pdf (123098 bytes).

LESCOPE98 : Visualizing Dynamic Power System Scenarios for Data Mining, LESCOPE98, Halifax (NS), June 1998, slides (351583 bytes).

IEEEWM98 : Artificial Intelligence Methods for Voltage Stability Assessment, IEEE PES Winter Meeting, Tampa (Fl), February 1998, slides of presentation to the Power System Stability Subcommittee (452086 bytes).

KDDLyon97 : Data mining and KDD Winter School, University of Lyon, Lyon (Fr), December 1997, slides of presentation (813919 bytes).

CPSPP97 : Tutorial on Intelligent Systems and their Power System applications, IFAC-Cigré Symp. on Control of Power Systems and Power Plants, Beijing (PRC), August 1997, course notes (330583 bytes).

PICA97 : Tutorial on Automatic Learning Methods. Application to Dynamic Security Assessment, IEEE Power Industry Computer Applications Conference, Columbus (Oh), May 1997, course notes (530313 bytes).

Software :

Back to top of this page PEPITo: This is a data mining software originally written in GCL (Gnu Common Lisp) and named GTDIDT. It is commercialized by the spin-off company PEPITe. Follow the link to learn more about it and get free demo versions. version.

Links :

Back to top of this page Research unit of Bioinformatics and Modeling at GIGA-R

http://www.giga.ulg.ac.be/jcms/c_5415/giga-systems-biology-chemical-biologyThematic research unit of systems biology and chemical biout logy at GIGA-R

Alma-In-Silico project

Back to Stochastic Methods home page Back to Institut Montefiore home page Back to GIGA home page Back to the ULg home page

Last update: Fri May 13 16:26:28 MEST 2005