News:

Workshop on Prediction in Complex Networked Systems: Focus on Epilepsy took place 13.-14. 12. 2018.

Complex systems

Behaviour of complex systems, typically consisting of many interacting elements, cannot be explained by a simple extrapolation of the laws describing the behavior of a few elements. Therefore it is important to investigate how relationships between system’s parts give rise to its collective behavior and how the system interacts and forms relationships with its environment. The study of complex systems regards collective, or system-wide behavior as the fundamental object of study. Therefore complex systems can be understood as an alternative paradigm to reductionism, which attempts to explain systems in terms of their constituent parts and individual interactions between them.

As an interdisciplinary domain, complex systems draw contributions from many different fields, such as the study of self-organization from physics,  spontaneous order from the social sciences, chaos theory and graph theory from mathematics, adaptation from biology, and many others. It follows that complex systems, as a research field, strives to solve open problems in diverse disciplines, including statistical physics, information theory, nonlinear dynamics, anthropology, computer science, Earth sciences, sociology, economics, psychology, and biology.

Key research trends in our field

The key trends correspond to main scientific and technological challenges in complex systems research:

• the need for reliable methods for complex systems analysis
• the strive for understanding the systems at multiple spatial and temporal scales
• the availability of increasingly large observational/experimental datasets and the related need for employment of high-performance computing and effective algorithms
• the need for integration of data-driven and theory-driven approaches in complex system modelling
• the ever-increasing inter-disciplinarity related to modelling interaction between complex systems

Vision

The department focuses on high-impact research in selected key problems areas:

• Development and thorough assessment of emerging complex systems data analysis methods and their utilization in societally relevant application areas
• Study of interactions across temporal scales in key application areas
• Efficient computation based on large amount of heterogeneous data leading to high computational demands. The problem includes areas of high performance computing as well as analysis of algorithm complexity.
• Development and optimization of frameworks integrating data and realistic theoretical priors
• Developing physically realistic models that bridge the gap between traditional application fields

Applications

The theoretical research in the department is closely related to research in a range of basic as well as applied research in diverse science fields, in particular:

• neuroscience
• climatology
• environmental modelling
• computer security

Seminars

The department organizes an irregular seminar with both local and international speakers.

Current projects

• Nonlinear interactions and information transfer in complex systems with extreme events
• Timing of the spatial scene processing in the dorsal and ventral visual stream of the human brain.
• URBI PRAGENSI Urbanization of weather and air quality forecast and climatic scenarios for Prague
• Urban Adaptation Challenges: Promoting Sustainable Planning Using Integrated Vulnerability Analysis
• Functional and structural reorganization of brain networks after stroke: implications for diagnosis and therapy of associated comorbidities.
• National Competence Center – Cybernetics and Artificial Intelligence

Selected previous projects

• MovieBrain
• ClimaNet
• EpiDyn
• CompClass
• BrainSynch
• NEST BRACCIA
• InterClimate