I am working on hybridization of Evolutionary Algorithms (EA) in a data mining context. Currently, I am co-supervising Romaric Pighetti with Pr. Precioso in the combination of SVM and EA for mining large scale image databases to deal with Content Based Image Retrieval.
I also investigated the use and adaptation of Evolutionary Computation (EC) for considering user preferences via Eye-Tracking technology in Interactive EC, water current prediction in Hydrology, abnormalities detection via NeuroEvolution in flights boarding, and more recently plant mining and flavors/olfactive receptors relationships (QSAR) in Chemistry…
Before 2007, I was interested by Computer Aided Design, Collaborative Design and Geometric modelling for manufactured products.
Evolutionary Algorithms (EA) are nature inspired and stochastic algorithms that mimic Darwin theory for problem optimization. The particularity of EA is its capacity to deal with multi-objectives (i.e. maximizing profits while minimizing costs), multi-modality (several best solutions) as the algorithm considers a population of solutions, discrete or continous optimization, dynamic optimization and many others fundamental problems… As data mining deals now with Big Data, it is natural to consider EA for optimizing models (neural network, association rules, decision trees or SVM…) produced by a mining or a learning process. They can also be considered for hybridation.
A recent overview of EAs by Thomas Bartz-Beielstein, Jurgen Branke, Jorn Mehnen and Olaf Mersmann in 2014.
Here is a list of domains where EA have been applied.
Most of my scientific production is refered by which give us simple biblio analytics there.
List of Evolutionary Computation Conferences ordered by upcoming deadlines.
Industrial Collaborations with
I participated to following past projects: