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Research grants

Does white Matter Matter?

This project aims to uncover how white matter alterations impact brain function in schizophrenia, using innovative whole-brain modeling and advanced neuroimaging techniques.

Optimizing the energy portfolio to increase the use of renewable resources (Lancelot GDS)

The goal of this project is the development of a comprehensive Lancelot GDS (Generation Dispatch Systém) optimization tool for power flexibility aggregators to increase the use of renewable resources.

Natural and Anthropogenic Georisks

The main research objective of the project entitled Natural and Anthropogenic Georisks is to understand natural and man-made threats, hazards, and risks in the Earth's upper spheres, to explore their causes and to quantify their potential impacts on human society and infrastructures.

Potential replacement vegetation modelling for nature conservation (NaPoVeg)

The proposed project takes a new approach to vegetation modelling, which will allow for different scenarios of landscape change impacts on vegetation and species diversity. This will help to promote an environmentally (biodiversity) but economically sustainable use of resources.

Climate-Resilient Development Pathways in Metropolitan Regions of Europe (CARMINE)

The frequency and intensity of climate and weather extremes associated with anthropogenic climate change are increasing and will challenge us in terms of adaptation strategies at the local level. The project “Climate Resilient Development Pathways in Metropolitan Regions of Europe (CARMINE)” bridges the local and regional scales by providing impact-based decision support services.

Research of Excellence on Digital Technologies and Wellbeing

The DigiWELL project responds to research challenges in key areas of the rapidly evolving domain of digital technologies aimed at promoting physical, mental and social wellbeing. Due to the biopsychosocial perspective we take in the project, the project is interdisciplinary in nature.

Brain dynamics (BRADY)

The project is focused on the development of computational models of brain activity that capture the dynamics of the brain at different time scales. The goal of the project is to develop research in the field of applied computational neuroscience in the Czech Republic, especially through the implementation of top research, strengthening ties to top foreign workplaces, developing the personnel capacities of the involved research teams and strengthening their experimental and computational capacities.

Social and motivational factors of study and their influence on study results in tertiary education with a focus on technical fields (STUFEDU)

The project aims to create recommended procedures for effective work with social and motivational factors affecting study results. It is elicited from interdisciplinary research with a core in robust sociological analysis, which will be broadened by machine learning and AI methods. The unique connection of various sources and types of data (quant. and qual.) with the background in various disciplines.

Neural networks realtime forecasting of variable baseline for the power equipment at HV, LV voltage levels (NNRF)

The content of the project is the development of a software solution capable of meeting the requirements for predicting a variable baseline according to ČEPS standards for a wide range of technologies on the consumption side and on the production side. The software solution - thanks to the innovative baseline prediction procedure - will significantly increase the possibility of involving these technologies in the provision of support services.

Symmetries of brain connectivity

Symmetry of the human brain (and the lack thereof) has been a matter of prominent debate since the report of the left-hemispheric dominance of language by Broca in 1865. Functions including memory, perception, learning, spatial cognition, attention, emotion processing and motor skills show degree of hemispheric specialization, and disrupted brain anatomy and more recently connectivity asymmetry has been associated with neuropsychiatric disorders such as schizophrenia.

From Biological Neural Networks to Next-Generation Whole-Brain Models

Tento projekt se nachází v oblasti počítačové neurovědy, která spojuje různé obory jako neurověda, aplikovaná matematika a informatika.

Research Infrastructure for Fermilab Experiments

The FERMILAB-CZ is devoted to Czech collaboration with the U.S. national laboratory Fermilab, the primary concern of which is the research of elementary particles. The core of the present Fermilab research programme is the neutrino experiments, including NOvA and DUNE experiments. FERMILAB-CZ's main knowledge expertise is the detector laboratory, which is engaged in the design and construction of detectors, and the mathematical expert group, which is involved in the development and application of advanced statistical and deep machine-learning artificial intelligence algorithms for data analysis.

Hodnocení chování automatizovaných vozidel z pohledu dodržování etických a právních principů ve smíšeném provozu (EBAVEL)

Etice provozu autonomních vozidel se v poslední době věnuje velká pozornost, neboť se jedná o technologii, která má potenciál výrazným způsobem ovlivnit společnost.

Coalition and Epistemic Logic: An Intensional Approach to Groups

The project will lift an important and up to now largely overlooked idealization in logical models of group knowledge and action - the extensional view of groups where a group is reduced to the set of its members. Consequently, groups change identity when their membership changes, any uncertainty regarding who is in a given group is ruled out and the structure of groups is not reflected.

Proof analysis AND Automated deduction FOr REcursive STructures

Mathematical induction is one of the essential concepts in the mathematician's toolbox. Though, its use makes formal proof analysis difficult. In essence, induction compresses an infinite argument into a finite statement. This process obfuscates information essential for computational proof transformation and automated reasoning.

Case studies design for a micro-climate modeling

During the last two decades, substantial progress in modelling urban microclimate processes has been associated with newly developed models. For the model validation, the precise and valid meteorological data represent the necessary information. This project represents a platform for open discussion about micro-scale measurement campaigns and its necessity for a correct interpretation of measured and modelled results.

Data Visualization Under Uncertainity

The topic of the proposal lies in computational geometry which is a branch of theoretical computer science.

MOSAIC Modalities in Substructural Logics: Theory, Methods and Applications

Modal logics are a family of formal systems based on classical logic which aim at improving the expressive power of the classical calculus allowing to reason about “modes of truth”. The aim of the present proposal is to put forward a systematic study of substructural modal logics, understood as those modal logics in which the modal operators are based upon the general ground of substructural logics, weaker deductive systems than classical logic. Our aim is also to explore the applications of substructural modal logics outside the bounds of mathematical logic.

Predicting functional outcome in schizophrenia from multimodal neuroimaging and clinical data

Schizophrenia is a chronic, severe and profoundly disabling disorder. For every 100 individuals with schizophrenia, only 1 or 2 individuals per year meet the recovery criteria, and approximately 14% recover over 10 years, with poor functional outcome for 27% of patients. There is an urgent need to develop predictive models of outcome to be applied in the initial stages of illness and thus optimize and intensify intervention programs to avoid an aversive outcome.

Graph limits and beyond

The theory of graph limits is one of the most important recently emerged tools of discrete mathematics. It has led to breakthrough solutions of many old problems in extremal graph theory, theory of random graphs and in particular in connecting discrete mathematics to fields such as probability, real anf functional analysis and group theory.

Air quality Research, Assessment and Monitoring Integrated System (ARAMIS)

The main goal of the project is to develop methods of air quality control, methods of identification of air pollution sources and their share in air pollution concentrations with a focus on current main problems of air quality and difficult quantification of different types of pollution. Consequently, model tools need to be developed to identify dispersion of air pollution, both with regard to current concentrations but also with a view to future expansion.

Interactions and causality in complex systems

Nalezení příčin událostí a jevů v přírodě a ve společnosti je výzvou snad všech vědních oborů.

Turbulent-resolving urban modeling of air quality and thermal comfort (TURBAN)

The main aims of the international project are to: considerably improve spatial resolution and quality of the urban atmospheric environment assessment on the basis of state-of-the-art modeling, observation and data analysis technologies; improve and validate advanced modelling tools with focus on modelling of the turbulent flow in complex urban environment.

Models of non-invasive brain stimulation

Transcranial magnetic stimulation (TMS) is a tool that is used regularly in experimental and clinical research, as well as for therapeutic and diagnostic purposes.

Causal inference and interactions between Arctic sea ice and Eurasian winter climate

Discerning the cause from effect is the aim of many scientific disciplines.

Quasi-decidability of the first-order theory of real functions

Decision procedures for predicate logical theories play an increasingly important role in computer science, especially in combination with Boolean satisfiability solvers, that is, in SAT modulo theory (SMT) solvers. While there is a vast amount of current research on decision procedures for integers, real numbers, arrays, and many other theories.

Characterizing state repertoire and dynamics of spontaneous brain activity by neuroimaging methods

Current psychological theory provides complex description of mental functions and processes. It is generally accepted that mental functions have brain as their substrate, and that mental processes and states are reflected in brain activity dynamics. A rapidly developing area of brain research is the study of spontaneous brain activity with functional magnetic resonance imaging, allowing simultaneous measurement of activity dynamics of a plethora of brain networks.

GRADLACT: Graded Logics of Action

Propositional Dynamic Logic, PDL, is a well-known tool used in the logical analysis of discourse about action. Being based on classical logic, it cannot provide adequate formalization of discourse involving graded, vague and imprecise concepts. This project will develop and study versions of PDL more suitable for this task, so-called graded dynamic logics. The project will contribute to an elaboration of formal methods applicable in the theory of action and applied ethics.

Metamathematics of substructural modal logics

Classical logic models reasoning about Boolean combinations of atomic propositions. Modal logics extend it by adding propositional connectives (called `modalities') to allow reasoning about the modes of truth, such as `necessarily’, `is allowed', or `is known'. Conversely, substructural logics relax assumptions on logical atoms to allow reasoning about other interesting objects.

AppNeCo: Approximate Neurocomputing

Nowadays, modern AI technologies based on deep neural networks, whose computation is demanding on energy consumption, are implemented in devices with limited resources (e.g. battery powered cellphones). In error-tolerant applications (e.g. image classification), the use of approximate computing methods can save enormous amount of energy at the cost of only a small loss in accuracy.

Learning Synchronization Patterns in Multivariate Neural Signals for Prediction of Response to Antidepressants

The concept of synchronization of nonlinear dynamical systems will serve as basis for development of mathematical methods and computer algorithms for detection and characterization of interactions and dependence in multivariate nonlinear time series. Directional links and causal relations will be quantified using the tools of information theory.

Network modelling of complex systems: from correlation graphs to information hypergraphs

Development of methods for effective description of complex systems is a growing area of interdisciplinary research at the junction of cybernetics, informatics, mathematics and theoretical physics, with application to a range of scientific disciplines including neuroscience, sociology, economics, genetics, and ecology. One of the key problems is the robust characterization of the structure of interactions within a system based on the multivariate time series.