The extraction of relevant and meaningful information out of high-dimensional data is notoriously complex and cumbersome. The curse of dimensionality is a popular way of stigmatizing the whole set of troubles encountered in high-dimensional data analysis; finding relevant projections, selecting meaningful dimensions, and getting rid of noise, being only a few of them. Multi-dimensional data visualization also carries its own set of challenges like, above all, the limited capability of any technique to scale to more than an handful of data dimensions.

The actual focus of our group’s work is to use Visual Analytics in discovering patterns of high-dimensional data.

Publications