Ata Kaban is professor in Computer Science at the University of Birmingham. She holds a PhD in Computer Science (2001) and a PhD in Musicology (1999). She is a member of the IEEE CIS Technical Committee on Data Mining and Big Data Analytics, and vice-chair of the IEEE CIS Task Force on High Dimensional Data Mining.
Ata Kaban works in high-dimensional data analytics and statistical machine learning, currently focusing on the problems of the 'curse of dimensionality', and the gap between theory and practice. She has a major interest in techniques and methodologies for large scale data analysis, in particular random projections and other dimensionality reduction methods, and their potential use to better explain how high-dimensional learning works. For instance, pixel representation of images becomes increasingly high-dimensional due to advances of high-resolution measurement devices. At the same time their information content may increase at a somewhat slower rate. This makes image data sets particularly suited to form testbeds for the problem of detecting low-complexity geometric structures that facilitate learning in high dimensions.