Jaroslav Hlinka is the Head of the Department of Complex Systems at the Institute of Computer Science, Czech Academy of Sciences and also the Chair of the Institute's Council. His research interests lie in developing and application of methods for data-driven analysis of real-world complex systems, with main focus on human brain.

David Hartman is working on problems concerning complex networks with regard to reliable construction as well as emergence of stuctural phenomena. The corresponding application domains includes those in neurological research or climatology. Another reseach domain is analysis of symmetrical relational structures and particularly graph or colored graphs possesing ultrahomogeneous or homomorphism-homogenous property.

Pavel Sanda research focuses on modeling dynamics of biologically inspired neural networks. That includes both simple sensory circuits and more complex networks involved in coordinated activity of cortico-thalamic loop as well as the rules which govern synaptic platicity between the neurons in the modeled circuitry.

Helmut Schmidt’s research focuses on computational techniques to understand and reproduce the dynamics of biological neural networks, ranging from small-scale networks to the entire (human) brain. While the mainstay of this effort is computational modelling of neuronal circuits, he is also interested in developing new methods for time series analysis, especially model-based data analysis. Applications encompass neuronal information processing (working memory, language acquisition) as well as disorders of large-scale neuronal networks, especially epilepsy.

Anna Pidnebesna is working on modeling and analysis of real-world complex systems. Her main work is connected with developing and applying data analysis methods, frequently using connectivity matrices and sparse linear approaches. The human brain investigation is the main application part.

Arthur Matsuo is working on the development of time series data analysis methods using symbolization techniques, in particular the ordinal patterns symbolization, to be applied in the characterization of human brain data represented by EEG time series.

Nikola Jajcay is a computational neuroscientist focusing on biophysically realistic population models and heterogeneous whole-brain modelling. Besides the main focus, his research interests include causality in complex systems, biostatistics, data science & Bayesian approaches.

Jakub Kopal is currently working at the intersection of system neuroscience and genetics. His research interests include neuroscience and data analysis, with a particular focus on the role of connectivity in brain functioning.