About me


I am a junior researcher at the Institute for System Programming of Russian Academy of Sciences (ISPRAS), where I am working on my PhD thesis on Inferring latent attributes of social network users (supervised by Sergei Kuznetsov).

My main research focuses on the development of …

I started my research in visual analytics and information visualization during my diploma thesis with the title “Visualisation Toolkit for Contact Density Potentials within Amino Acid Neighbourhoods in Protein Structures”, which I wrote at the Max-Planck Institute for Molecular Genetics, Berlin.

The aim of visual analytics systems is to derive insights from massive, dynamic and conflicted data. The data analysis is thereby supported through adequate visualization and highly interactive interfaces.

In the context of biology, these vast amounts of data are a result of experiments as well as simulations of processes of single molecules over expression values of genes up to modeling of whole populations. The analysis of such data is particularly difficult, as they are often heterogenous, high-dimensional and do contain errors. Hence, there is an urgent need for adequate, modern visualizations and analysis techniques.

I’m particularly interested in the development of visual analytics systems for biological networks, like gene-regulatory, signal-transduction and metabolic networks. Moreover, I’m interested in the diverse kinds of attributes that may be associated to the nodes and edges of the network (graph). Further challenges for the visualization of biological networks or graphs in general are introduced, if the graph topology or the attributes of the graph are dynamic or fraught with uncertainty.

Therefore, I am also working on visual analytic approaches for dynamic graphs and networks in general, i.e., for graphs those topology or properties change over time.