RESEARCH INTERESTS

My research interests are Data Mining, Machine Learning and Mathematical Programming. I develop the new algorithms for data mining problems such classification, clustering and regression (linear and nonlinear). Using methodologies such as support vector machines, chunking and smoothing techniques allows us to get a very robust solution (prediction) for large datasets. I also apply these methods to solve many real world problems. An important aspect of my research is the use of data mining techniques in breast cancer prognosis.

My areas of research include:

Supervised and unsupervised learning
Multicategory learning
Support vector machines
Smooth technique for SVM
Large-scale nonlinear SVM
Medical application: Breast cancer prognosis