Research grants

Turbulent-resolving urban modeling of air quality and thermal comfort

TO01000219 2021 - 2023

The main aims of the 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; - improve methods for combination of observational and model data; - compare environmental effects of the selected impactful urban policy measures in Prague and Bergen; - equip public authorities with a set of tools to support urban governance: focus on air quality and thermal comfort. The specific results of the project are described in section Deliverables.

Understanding, Handling, and Exploiting Biases in Knowledge Graphs (BiasKG)

21-07402J 2021 - 2023

In computer science, especially in data science and artificial intelligence, bias is usually used to refer to an unintentional skew in a dataset or behavior of a program. This project primarily focuses on biases demonstrating as algorithmic biases, which affect many artificial intelligence applications, resulting, for example, in discrimination and underperforming models. We aim to study biases in knowledge graphs, which provide machine readable semantics for the emerging generation of AI applications. We want to take a dual look at the removal of bias from knowledge graphs by identifying the cases and scenarios in which removing biases results in an improvement, and in which cases removing the bias deteriorates the knowledge graph or machine learning model, since the bias should actually be considered a useful signal. The project will build on prior psychological research on cognitive biases to identify the pathways through which biases enter data and explore how they manifest. Methods for bias removal based on active learning and crowdsourcing will be proposed.

MOSAIC Modalities in Substructural Logics: Theory, Methods and Applications

2021 - 2024

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 and, in particular, in the areas of knowledge representation; legal reasoning; data privacy and security; logical analysis of natural language. This is a 4-year project in the framework H2020-MSCA-RISE-2020: Research and Innovation Staff Exchange.

Graph limits and beyond

21-21762X 2021 - 2025

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. In the project, we will study the foundations of the limit theory of graphs, graph norms, and connections to mathematical models of statistical physics.

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

21-17211S 2021 - 2023

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. A common method for system representation is using correlation matrix of the variables, treated as graph and studied using graph-theoretical metrics, in comparison with random graphs of matched size and density. Recent results show multiple issues of such approach: correlation matrices do not capture faithfully the interactions, neglect higher-order dependences, insufficiently capture the predictive power in multivariate nonlinear models and lead to a bias in key graph metrics. We shall move beyond the state-of-art and our recent results towards a more general and robust complex system characterization. The main aim of the project is to bring theoretical and methodological advances in complex network research by tackling four key challenges outlined in the abstract.

Theoretical foundations of computational psychometrics

21-03658S 2021 - 2023

Psychometrics, as a field concerning psychological, health-related, educational and other behavioral measurements, is the disciplinary home of number of statistical data science methods. This project studies theoretical and computational aspects of psychometrics with the aim to propose estimation and detection methods superior to traditional ones. Project focuses on two psychometric topics (estimation of reliability and detection of differential item functioning) and their extensions to more complex designs. Project also provides software implementations as well as simulated and real data examples demonstrating usefulness and superiority of the proposed methods. The theoretical and computational aspects and innovations improving psychometric algorithms covered in this project may have broader impact on statistical data science.

Supporting the internationalization of the Institute of Computer Science of the Czech Academy of Sciences

CZ.02.2.69/0.0/0.0/18_053/0017594 2020 - 2022

The Institute of Computer Science of the Czech Academy of Sciences will create a post-doctoral position for an excellent junior researcher from abroad. A research stay of a junior ICS researcher or a PhD student at a research institution abroad will take place. Two short-term visits of administrative or technical employees of the ICS at a research institution abroad will take place.

This project is co-funded by the EU.

City for People, not for Virus

TL04000282 2020 - 2021

The goal of our project is to create a software tool for simulation of social ties and anti-epidemic measures, which will enable to compare the efficiency of these measures with their impact on individuals as well as on society. The core of our tool is a network model of COVID-19 spread in the CR. Our model combines longitudinal sociological data from Life during pandemic survey (interactions, work and spare time activities, economic impact on households etc.) with demographic and epidemiological data. This way we estimate health, social, and economic impacts of various anti-epidemic measures (quarantine, contact tracing, local closures). The planned outcome will help municipalities, firms or hospitals to compare the effects of given measures on individuals and communities.

Air quality Research, Assessment and Monitoring Integrated System

SS02030031 2020 - 2026

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. Part of the research is also the development of laboratory methods for air quality evaluation, both methods of manual, isotopic analysis of elements in aerosol particle samples and methods of elemental analysis of aerosol particles. With regard to the impact on the health of the population, the impact of ultrafine particles will be evaluated at 5 localities in the Czech Republic, also with regard to external influences such as meteorological conditions. The project also includes estimation of the fraction of fog and icing in the total atmospheric deposition and the outputs will be used for quantification of the ozone effect. An interesting result of the project will also be the maps of phytotoxic doses of ozone for various plants. The impact of transport is apparent across the whole project, both on the health of the population and on the pollutant and greenhouse gas emissions. An unforgettable task of this project is the development of methodologies and emission factors used in the preparation of emission balances in relation to the international requirements of the EU and the UN Conventions. Also, data standards for reporting obligations introduced by Act 25/2008 Coll. will be developed, which will be an essential element of the subsequently developed comprehensive information system on air quality.

Collaboration on Fermilab experiments 2

CZ.02.1.01/0.0/0.0/18_046/0015954 2020 - 2022

The project follows the OP VVV project CZ.02.1.01/0.0/0.0/16_013/0001787 of similar name and abbreviation. Its objective is the continuation of reconditioning and increasing the computing and storage capacity for processing data from experiments in Fermilab. The aim is to improve the infrastructure to gain new scientific knowledge in collaborative experiments in Fermilab. This project is co-funded by the EU.

This project is co-funded by the EU.

Substructural Modal Logics for Knowledge Representation

CSIC-20-12 2020 - 2021

Modal logics are a well-known tool in Artificial Intelligence and Computer Science in general, used for representing and reasoning with information about possibility and necessity, time, actions, knowledge and abilities of agents and other “modes of truth”. However, their versions based on classical logic have limitations, for example when it comes to modal reasoning in contexts involving graded predicates, resource-sensitivity, cognitively limited agents etcetera. This project will contribute to a systematic development of the theory of modal logics based on a large class of logics weaker than classical logic, namely, substructural logics. Teams from IIIA-CSIC, Barcelona, and ICS-CAS, Prague, will build on their expertise in modal and substructural logics and their previous collaborations, and achieve the project goals through a two-year period of intensive collaboration, reinforced by mutual research visits and workshops.

Daily evolution of brain connectivity during the pre-ictal period in intracerebral recordings of epileptic patients

Mob_France 2020 - 2021

Epilepsy is a chronic neurological disorder affecting around 50 million people worldwide, characterized by repeated brain seizures, the neurophysiological mechanisms of which are still largely unknown. Recent studies show the existence of an altered brain state before seizure. We aim to identify changes in brain connectivity that correspond to these differences in brain states during pre-ictal period. We recorded high-quality intracranial EEG as well as scalp EEG data from 74 patients, each monitored for more than a week. The aim is to understand the changes in interactions between brain areas as the brain is approaching a seizure. Based on such interactions we strive to identify markers of ictogenesis that can help seizure prediction and treatment. The proposed project will deepen the current cooperation between both institutes.

Interactions and causality in complex systems

2020 - 2025

Street-level urban microclimate modelling using LES principle in north-american cities

MSM100302001 2020 - 2021

Human thermal environment is in researchers’ interest for several decades. At the same time, with increasing computation power is possible to solve more complex problems. One of them, urban climate, demands on resolution raises the question, whether turbulence should be treated as a (partly) resolved or as a (complete) sub-grid scale process. Atmospheric modelling of urban areas usually considers a limited number of relevant processes, alternatively it is performed with coarser resolution which cannot properly describe the conditions in street canyons. PALM-4U is the first open-source meteorological model based on large-eddy simulation (LES) principle with implementation of the most of urban canopy related processes. The recent version of PALM-4U include Urban Surface Model (USM) and Radiative Transfer Model (RTM), necessary modules for calculation of MRT for biometeorology module. Those features open new challenges in street-level scale research of biometeorology.

Random discrete structures

20-27757Y 2020 - 2022

The project focuses on problems in the overlap of discrete mathematics and probability theory. We consider basic discrete structures: graphs, digraphs, trees, uniform hypergraphs, which in applied areas are used as abstract models for networks, population dynamics, etc. We will study randomly generated discrete structures from a theoretical perspective. Focusing on random variables which count the number of certain substructures (e.g., copies of a given graph), we seek answers to the following questions: what are their asymptotic distributions, how likely are events that these random variables deviate significantly from their expected values. Among the objectives of the project is to study the similarity between the random regular graph and the binomial graph by resolving the Sandwiching Conjecture of Kim and Vu; estimating the upper tail probability for small subgraph counts in sparse random graphs; determining the limit distribution of functionals (e.g., number of large matchings, maximum independent set) in random graphs and Galton-Watson trees.

Modelling the sleeping brain: towards a neural mass model of sleep rhythms and their interactions

CZ.02.2.69/0.0/0.0/19_074/0016209 2019 - 2021

Memory consolidation, a prominent example of higher cognitive processes, relies on two important neural phenomena: slow- wave sleep with a wealth of distinct rhythms, and cross-frequency coupling between these rhythms. Neither of these processes is, to this day, fully understood. However, according to the two-stage model of memory consolidation, the interplay between slow oscillations and sleep spindles by means of phase-amplitude coupling, as well as the interplay between sleep spindles and hippocampal sharp-wave ripples, seem to promote neural plasticity and initiate a cortical- hippocampal dialogue that leads to experience replay and, ultimately, migration of newly encoded memories to longer-lasting storage. The overall aim of this project is to shed light on the slow oscillation-spindle interplay using a biologically realistic neural mass model and, additionally, reproduce the cross-frequency phenomena.

This project is co-funded by the EU.

Structural properties of visibility in terrains and farthest color Voronoi diagrams

GJ19-06792Y [Registered results] 2019 - 2021

This research project deals with two popular topics in Combinatorial and computational geometry: visibility and Voronoi diagrams. The first concrete topic is visibility in terrains in the presence of multiple observers. This variant has received much less attention than the case of a single guard and presents a great number of applications. Given a terrain and a set of observers, the most fundamental question is being able to describe which parts of the terrain are visible by at least one of the observers; we will try to improve on the current fastest algorithms to solve this problem. We also plan to study approximate versions of the visibility maps, and realistic settings where the observers or the terrain satisfy some natural assumptions. The second topic concerns the farthest color Voronoi diagram, which has not been as studied as other types of Voronoi diagrams. We intend to get new insights on the structure of this diagram, and explore their algorithmic consequences.

National Competence Center - Cybernetics and Artificial Intelligence

TN01000024 [Registered results] 2019 - 2021

The NCK KUI project aims to create a national platform for cybernetics and artificial intelligence which interlinks research and application oriented centers of robotics and cybernetics for Industry 4.0, Smart Cities, intelligent transport systems and cybersecurity. The connection of innovation leaders will raise effectivity of applied research in key areas, as advanced technology for globally competitive industry, ICT and transportation for the 21st century. NCK KUI is closely related to application sector and enables cross-domain collaboration, innovation development and technology transfer.

Embedding, Packing, and Limits in Graphs

GA19-08740S [Registered results] 2019 - 2021

Graphs are among the simplest mathematical structures. They forms the foundation of much of Computer Science and their importance grew enormously with the development of computer networks. In this project, we focus on central problems from extremal graph theory, as well as the recent related area of limits of graphs. We shall exploit classical methods from extremal graph theory, as well as probabilistic and analytical methods. Our main topics are embedding problems, packing problems, and the study of graph limits via a weak* topology approach.

FoNeCo: Analytical Foundations of Neurocomputing

GA19-05704S [Registered results] 2019 - 2021

The computational paradigm has recently been shifted towards intelligent information processing which can be demonstrated by tremendous success of (deep) neural networks (NNs) producing state-of-the-art results in artificial intelligence. The majority of techniques used in NNs are of heuristic nature and therefore only partially theoretically justified. FoNeCo is a basic research project whose ambition is to contribute to the development of analytical foundations of selected practical neurocomputing models. Its aim is to characterize the computational power of subrecursive NNs between integer and rational weights using quasiperiodicity, and bio-inspired NNs based on synfire rings, to study approximation properties (e.g. model complexity) and robust fitting of various regression NNs, and to analyze the complexity of loading deep NNs. The analysis of respective NN models will be the basis of new architectures and more efficient, reliable, and theoretically-founded learning algorithms which will be implemented as open-source software and experimentally tested on benchmark problems.

Boolean Representation Languages Complete for Unit Propagation

GA19-19463S [Registered results] 2019 - 2021

This is a basic research project in which we plan to work on problems in the area of knowledge compilation. We consider a particular case of knowledge compilation where the knowledge base is represented by a boolean function, usually in a conjunctive normal form (CNF) formula. We plan to study a compilation of such a formula into another CNF formula which is complete for unit propagation. More precisely, we will consider compilation into the target language of unit refutation complete formulas (URC), the language of propagation complete formulas (PC), and the corresponding variants of encodings with auxiliary variables, namely URC and PC encodings. The goal of this project is to solve theoretical questions related to compilation into URC or PC representation or encoding and develop a compiler for this task. To this end we shall develop and test algorithms and heuristic for automatic compilation. The outputs of this project will be published in journal and conference papers.

Timing of the spatial scene processing in the dorsal and ventral visual stream of the human brain

GA19-11753S [Registered results] 2019 - 2021

The project’s focus is the dynamics of brain processes during spatial scene processing in the dorsal and ventral visual streams. While the dorsal stream, going from visual cortex to parietal lobe, processes mainly the spatial information, the ventral stream, going to the temporal lobe, is focused on object recognition. The level of separation of the two streams and their interconnection is not fully established. Both streams converge in the temporal lobe, enabling the emergence of the spatial representation containing orientation marks, but the precise localization and dynamics of this connection is unclear. The project will examine several models of cooperation between these visual streams and the information flow between occipital, parietal and temporal lobe and retrosplenial cortex. Using intracranial recordings in epileptic patients, we will determine the time windows of activation and synchronization of these brain areas with high time resolution. The project will bring results concerning the dynamics of brain processes fundamental for visual scene processing theories.

Nonlinear interactions and information transfer in complex systems with extreme events

GA19-16066S [Registered results] 2019 - 2021

Theory of synchronization of nonlinear dynamical systems and information theory meet in effort to understand cooperative behaviour in complex systems. Yet features such as multiscale dynamics and fat-tailed probability distributions have not been adequately addressed in development of tools for uncovering interactions and causal information flow from experimental time series. In this project we will employ and further develop methods of information theory and superstatistics in order to detect and quantify internal dynamics and information flow in real-world complex systems in which extreme events occur. In particular, we will study Shannon and Renyi information transfer in multivariate and multiscale time series and advance the application of the superstatistics paradigm in complex dynamics with non-Gaussian fluctuations. The primary application ground will be the multivariate meteorological data reflecting the changing Earth climate, evolving on multiple time and space scales.

Introduction of targeted protection of cereal crops against insect pests in precision farming

QK1910281 [Registered results] 2019 - 2022

This project will develop statistical tools for prediction of crop pests in the age of precision agriculture. The developed methodologz will be based on modern semiparametric and dznamical modeling in the GAM framework. The models will be developed in several variants and the most suitable model will be selected by formalized statistical procedures. Based on the validated model, we will construct both routine predictions and derive recommendations for crop management timing.

Urban Adaptation Challenges: Promoting Sustainable Planning Using Integrated Vulnerability Analysis

TL01000238 [Registered results] 2018 - 2022

The main objective of the proposed multidisciplinary project is to conduct vulnerability analysis and to create a methodology of integrated vulnerability assessment of cities and their inhabitants to temperature extremes, using the classification of urban surfaces (delivered 02/2022), aiming on supporting the adaptation planning and adaptation measures in cities. Detailed spatial vulnerability assessment will be performed for three pilot cities (Prague, Brno, Ostrava), using climatological analysis and participatory approaches, considering projections of future developments (climatological scenarios, land cover changes, socio-demographic trends), with an output of specialized vulnerability maps. The integrated assessment aims to contribute to the sustainable urban planning in Czechia.

Capabilities and limitations of shallow and deep networks

GA18-23827S [Registered results] 2018 - 2020

The goal of the project is to contribute to development of neurocomputing by combining theoretical and experimental research investigating capabilities and limitations of shallow and deep artificial neural networks from the point of view of their model complexity and robustness of learning.

Reasoning with graded properties

GA18-00113S [Registered results] 2018 - 2020

The goal of the grant is to create logical framework to model reasoning with graded predicates. We distinguish several types of such predicates, discuss their ubiquity in rational interaction and the logical challenges they may pose. We plan to utilize mathematical fuzzy logic as a set of logical tools that allow to model reasoning with graded predicates and concentrate on a philosophical account of the vagueness problem that makes use of these tools. Other aim is to generalize this approach to other kinds of graded predicates a lay foundation for a general research program towards a logic-based account of reasoning with graded predicates.

Fusion-Based Knowledge Discovery in Human Activity Data

GA18-18080S [Registered results] 2018 - 2020

The proposed project of basic research in the area of multimedia data mining attempts to contribute to further development of methods for knowledge discovery in video data recording human activities. It concentrates on the one hand on combining knowledge about the detected human bodies, their parts and their motion with other knowledge obtainable from the available data, such as knowledge about scene, context, or person-object interactions, on the other hand on research into different ways of fusion of multiple classification or regression models during such knowledge discovery, including fusion based on deep artificial neural networks. These objectives are supported by experimental equipment and by the composition of the project team. At the Faculty of Information Technology of the Czech Technical University, a modern Image Processing Laboratory has been recently inaugurated, and the team includes, apart from the head of the laboratory and several PhD students performing in it their research, also two internationally recognized researchers in the area of data mining.

Non-classical logical models of information dynamics

GJ18-19162Y [Registered results] 2018 - 2020

Reasoning about modifications of information available to cognitive agents (about information dynamics) is an essential part of many everyday activities. A better understanding of mechanisms of such reasoning is important both from the practical viewpoint and in the context of epistemology. The project studies logical models of information dynamics based on non-classical logics. These models are mode adequate that the standard model based on classical logic. Their advantages include a better representations of information modifications resulting from reasoning of logically imperfect agents, a better representation of graded acceptance of information and the fact that they are able to model dynamics of questions in the context of logically imperfect agents. The project will provide a complete picture of some of these models. We will provide new results concerning their properties and study their applications in epistemology. The project will therefore lay a technically sound foundation of future research in the intersection of formal epistemology and philosophical logic.

Functional and structural reorganization of brain networks after stroke: implications for diagnosis and therapy of associated comorbidities

NV17-28427A [Registered results] 2017 - 2021

Cognitive impairment and epilepsy are the most common and serious post-stroke comorbidities. They have far-reaching impacts on patient health status and decrease the efficacy of rehabilitation and delay the recovery. Severe attention deficits, post-stroke dementia or epilepsy are comorbidities which have failed to be explained in terms of being a direct conseguence of localized damage to specific brain structures. Converging evidence suggests that understanding the emergence of these comorbidities requires radically new research paradigms that consider the impact of stroke on whole-brain connectivity. In this multidisciplinary project we seek to brain areas with high connectivity and information transfer - network hubs. Application of such a fundamental and innovative framework has potential to advance our understanding of stroke consequences and to develop early, network-targeting. therapeutic interventions to prevent or ameliorate these detrimental comorbiditiens.

Effectiveness analysis of prenatal diagnosis of congenital malformations and survival of children born with a birth defect in 1994-2015

NV17-29622A [Registered results] 2017 - 2021

Retrospective analysis of the consecutive data on prenatally and postnatally diagnosed cases of birth defects (BD) diagnosed in the Czech Republic between 1994 and 2015. We will perform 1) an analysis of incidences of prenatally diagnosed cases of BDs in the Czech Republic; 2) an analysis of incidences of postnatally diagnosed cases of BDs in the Czech Republic (incidence in births); 3) an analysis of effectiveness of prenatal diagnosis according to the individual diagnoses of BDs; 4) an analysis of stillbirth rate, perinatal neonatal and infant mortality in children with BDs.