Rafael Ballester

Rafael Ballester

Postdoc/Oberassistent - BIN 2.C.05

Phone: +41 44 635 43 67



My research focuses on visualization and analysis of complex and/or large-scale multidimensional data sets, e.g. micro-computed/synchrotron tomography, simulation parameter spaces, surrogate models, etc. The tool I use is tensor decompositions (mostly the tensor train (TT), the Tucker model, and other tensor networks): they lend themselves very well to data manipulation in the compressed domain, including derivation/integration, convolution, element-wise operations, statistical moments, etc. I used these in my PhD for multidimensional compression, filtering, surrogate modeling, sensitivity analysis, and feature extraction, among others.

Related techniques include 3D/4D multiresolution representations, progressive tensor rank reconstruction and out-of-core memory management.

More details on the scientific visualization aspect:

More details on surrogate modeling/high-dimensional learning: