DW-MRI Anlysis	In our group, we are mainly focused on the Multi-Tensor Model for local reconstruction, which has been proved to be very accurate in recent comparative studies. Some of our research lines are: Local reconstruction Response function simulation White matter fiber bundle segmentation
3D Face Recognition	My work on 3D-Face Recognition is mainly focused on the development of algorithms for feature selection and dimensionality reduction. Such algorithms are necessary because of the large number of variables we typically work with in 3D Face Recognition (hundreds of thousands). I am mainly interested in the connection between Bayesian formulations in image processing (e.g. denoising and segmentation) and algorithms for feature selection. In my work I explore the Bayesian formulation of the feature selection task under the smoothness prior for 3D Face Recognition, 3D Facial Expression Recognition and ethnicity-based subject retrieval.
Image Processing	I am interested in algorithms for image filtering and segmentation. My work is mainly based on Markov-Random Field Models. My main contribution was the development of the original optimization algorithm for fitting the Entropy-Controlled Markov Measure Field Model (EC-QMMF) developed in our group, which has been successfully applied for a variety of image processing tasks like segmentation of T1-Brain-MRI images, disparity estimation from stereo-pair images, image denoising and range-image segmentation among others.
Personal interests	In this section I put some material about topics, other than my research, that I have found to be fascinating or at least useful Convex Analysis and Optimization: things experts never say because of being trivial, but we dummies don't get right away Programming Competitions: some notes and implementations of algorithms I have found to be very interesting Software tools: notes on portability issues I have had with useful tools (MUMPS, ARPACK, CLAPACK, MRTRIX)