Institute of Computer Science

The Czech Academy of Sciences

The Czech Academy of Sciences

"A computer lets you make more mistakes faster than any other invention with the possible exceptions of handguns and Tequila." - M. Ratcliffe

(grants in alphabetical order)

The subject of the project is to improve the methods for data processing of Fermilab experiments and design of new analyzing procedures of these data based on machine learning algorithms and artificial intelligence. The goal is to continually improve the potential of acquiring new scientific knowledge on collaborative experiments in Fermilab, the development of new innovative data processing methods in high energy physics and the improvements of computing infrastructures of participating experimental institutions in Fermilab. The target group of the project results are the researchers of universities and research and development experts in general. From project outputs benefit experts from all research institutions cooperating experiments in Fermilab.

01. 04. 2017 - 31. 03. 2020

Theoretical computer science uses mathematical methods in order to clarify some of the most important notions used in computer science and, therefore, it is a key research area within computer science. Logic is an important part of theoretical computer science, focusing on modelling bodies of information and ways how agents use them in reasoning. So called non-classical logics, alternatives to classical logic, aim at a better representation of various aspects of information and reasoning than the representations based on classical logic (these aspects include vagueness, incompleteness and inconsistency of information or limitations of reasoning agents). Within this project, the Institute of Computer Science hosts three researchers working on non-classical logics and their applications to specific problems in theoretical computer science. The overall goal of the project is to study (i) applications of non-classical logics in program verification, (ii) applications of non-classical logics in the study of weighted structures (with focus on the Valued Constraint Satisfaction Problem) and (iii) non-classical logics with so-called generalized quantifiers (with focus on their computational properties).This project is funded by the European structural and investment funds within the Operational Programme Research, Development, Education.

01. 05. 2018 - 30. 04. 2020

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.

01. 01. 2019 - 30. 12. 2022

One of the key directions of data mining, particularly important if human-comprehensibility plays a role, is the extraction of rules from data. The project aims at rules with consequents corresponding to numerical variables. In spite of the ubiquity of such variables, rules extraction is not yet as mature for them as for classification and association rules. The main objective of the project is to develop a framework to enable assessing different algorithms for the extraction of rules with numerical consequents from a given dataset. Traditional algorithms view consequent variables as responses and antecedent variables as regressors of regression models. They are complemented by emerging algorithms of computational topology. The framework will be based on metalearning, i.e., learning from metadata about the past performance of the algorithms on datasets with similar values of metafeatures. Metalearning has been for several decades successfully used in classification and some other areas of data mining, but its application to the extraction of this kind of rules is novel. Targets: development of a metalearning framework for the extraction of rules with numerice consequents, search for metafeatures in two selected application domains, research into robust metalearning, validation of the metalearning framework on metadata from both application domains.

01. 01. 2017 - 31. 12. 2019

Classical mathematical logic, built on the conceptually simple core of propositional Boolean calculus, plays a crucial role in modern computer science. A critical limit to its applicability is the underlying bivalent principle that forces all propositions to be either true or false. Propositional logics of graded notions (such as tall, rich, etc.) have been deeply studied for over two decades but their predicate extensions (accommodating, among others, modalities and quantifiers) are still only very partially developed and scarcely applied to particular komputer science problems. The overall goal of the proposed project is to develop predicate graded logics in two complementary directions: (1) studying logical systems in full generality in order to provide a solid mathematical framework and (2) applying achieved results to three particular problems in computer science which heavily involve graded notions: representation of vague and uncertain knowledge, valued constraint satisfaction problems, and modelling of coalition games. We plan to develop predicate graded logics by giving them solid mathematical foundations and applying the achieved results to three particular computer science problems involving graded notions: management of uncertainty, valued constraint satisfaction problems, and modelling of coalition games.

01. 01. 2017 - 31. 12. 2019

RI serves for Czech contribution to particle physics research on experiments at Fermilab. It consists of experiments on which Czech physicists collaborate in Fermilab and of infrastructures of the Czech collaborating institutions.Members of RI work on the Fermilab's experiments NOvA, D0 and plan to join a new experiment in two years to contribute to its design and construction. In the Czech Republic it is a RCCPP computing farm and physics laboratory in FZU, cluster for artificial intelligence and neural networks algorithms in ICS and numerical and statistical computing servers at CTU. The whole infrastructure serves for particle physics experiments and for researchers for many years. The RI as top world research environment serves also for education of undergraduate and postgraduate students.

01. 01. 2016 - 31. 12. 2019

Ductile or brittle behavior of cracks is one of the key phenomena which may have a crucial influence on static and dynamic strength of mechanical structures utilizing bcc iron based materials, e.g. ferritic steels. Continuum predictions on ductile/brittle behavior of a central crack under biaxial tension show that the change of called T-stress can change ductile crack behavior to brittle crack extension. We utilize 3D atomistic molecular dynamic (MD) simulations in bcc iron at various temperatures to verify predictions on ductile-brittle transition caused by T-stress. It will be done for central cracked specimens under biaxial tension and as well for edge cracked samples under uniaxial tension, available for experiments. The topic is important for reactor pressure vessels and interpretation of fracture experiments. Another important aim is interconnecting with first-principles calculations for model clusters of restricted size, pointed at cohesive energy, tension and shear strength, atomic configurations and forces at defects,determining interatomistic potential parameters for MD.

01. 01. 2017 - 31. 12. 2019

The project Urbi Pragensi addresses improvements and implementation of the weather prediction and air quality prediction for region of Prague together with more detailed assessment of impacts of climate change in the city. The prediction improvements are achieved by utilization of the modern methods based on incorporation of parameterization of urban level processes into the high resolution atmospheric models. Complementary approach are microscale simulations which can expose in detail situation in given parts of the town with substantial burden of heat island and air pollution. This can contribute to estimation of the health risks as well as to efficiency assessment of proposed mitigation measures. ICS is involved in works on concept KK1 (meteorological prediction), KK2 (air quality prediction) and it is the coordinator of the concept KK4 (microscale simulations). The main partner of the project is Charles University in Prague, another partner is Czech Hydrometeorological Institute in Prague. In the scope of the project, we tightly collaborate with other Czech and foreign academic institutions (from Germany and Finland). We also tightly cooperate with principal intended users of the project outputs (e.g. Prague municipality and Prague Institute of Planning and Development).

01. 01. 2018 - 30. 06. 2020

(end year - alphabetical order)

- SYSMICS: Syntax meets semantics: Methods, interactions, and connections in substructural logics

- Center of Excellence - Institute for Theoretical Computer Science
- Extremal graph theory and applications
- Iterative Methods in Computational Mathematics: Analysis, Preconditioning, and Applications

- Advanced random field methods in data assimilation for short-term weather prediction
- An Order-Based Approach to Non-Classical Propositional and Predicate Logics
- Automated Knowledge and Plan Modeling for Autonomous Robots
- Estimation of psychometric measures as part of admission test development
- Model complexity of neural, radial, and kernel networks
- Modelling vague quantifiers in mathematical fuzzy logic
- Simulation-Based Computation of Robust Invariants of Hybrid Dynamical Systems
- Spolupráce na experimentech ve Fermiho národní laboratoři, USA
- Totally ordered monoids
- zkouska

- Constructing Advanced Comprehensible Classifiers
- Klimatické sítě: Rozmanitost měřítek dynamiky a interakcí v atmosféře Země
- Large-scale dynamics and critical transitions in neuronal networks and their role in limbic seizure genesis
- Modeling of Complex Systems by Soft-Computing Methods
- Personality and spntaneous brain activity during rest and movie watching: relation and structural determinants

- Algebraic Methods in Proof Theory
- Distribution and metric properties of number sequences and their applications
- Nanostructures with transition metals: Towards ab-initio material design

- A Multivalued Approach to Optima and Equilibria in Economics
- Game - theoretical approach to many - valued logics
- Geometry of associative structures
- Integrated Verification and Falsification of Hybrid Systems of Industrial Size
- Mathematical Fuzzy Logic in Computer Science
- NoSCoM: Non-Standard Computational Models and Their Applications in Complexity, Linguistics, and Learning
- 100 vědců do středních škol

- Application of artificial neural networks in systems for person
- Interactions, information transfer and complex structures in the dynamics of changing climate
- Learning of functional relationships from high-dimensional data
- Number theory and its applications

- Applications of Methods of Knowledge Engineering in Data Mining
- Decompositions of matrices with binary and ordinal data: theory, algorithms, and complexity
- Efficient Handling Non-linear Numerical Constraints Arising in Automated Reasoning about Rich Models of Computer Systems
- Greenhouse gases emission reduction using information technologies
- Interoperability of Future Web Services in the Web of Linked Data
- Logical Foundations of Semantics
- Logic-based fuzzy mathematics
- Model-Driven Evaluation of Design Desicion Impacts in Software Engineering
- Preconditioning and iterative solution of saddle-point problems
- Res Informatica
- Social Network of IT Specialists in Regions of Czech Republic
- Theory of Krylov subspace methods and its relationship to other mathematical disciplines
- Towards deeper understanding of Krylov subspace methods
- Web Semantization

- Analysis of negative impacts on driver attention
- BrainSync - Large Scale Interactions in Brain Networks and Their Breakdown in Brain Diseases
- Development of Methods for Solving Large Scale Nonlinear Programming and Nonsmooth Optimization Problems
- Extraterrestrial effects on atmospheric circulation in mid and high latitudes
- Logical Models of Reasoning with Vague Information
- Methods of Artificial Inteligence in GIS
- Úloha folátů v etiopathogenesi metabolického syndromu
- Universe of informatics

- Complexity of perceptron and dernel networks
- Decentralized control and communication
- Dynamic Formal Systems
- Intelligent Middle Agents for Mediation of Semantic Web Services
- Model complexity of large fuzzy rule-based systems and neural networks
- Neural Networks Learning Algorithms Based on Regularization Theory
- Verification of Hybrid Systems - Exploiting the Synergy with Underlying Constraint Solving Technology

- Advanced Remedial Technologies and Processes
- Algebraic, analytic and combinatorial number theory
- Centre of Biomedical Informatics
- Complexity of t-norm based logics - algebraic and proof-theroetical approach
- Dynamics of system aliances
- Institute for Theoretical Computer Science
- Interactive Information Portal for Algorithmic Mathematic
- Mathematical Foundation of Inference and Decision under Uncertainty
- Mathematical Modelling of Natural Gas Consumption for Small and Middle Clients
- Methods for Intelligent Systems and Their Applications in Datamining and Natural Language
- Realistic Application of Formal Methods in Component Systems
- Solution of large, sparse and nonsymmetric linear systems with Krylov subspace methods.

- A new approach to knowledge representation and exchange in concept and sensor networks
- Application of quantum informatics on PKI (Public Key Infrastructure)
- BRACCIA - Brain, Respiration and Cardiac Causalities in Anaesthesia
- Collegium Informaticum
- Development of numerical methods for solving large scale nonlinear programming problems
- Development of software system for solving large-scale problems of nonlinear and nonsmooth optimization
- Information technologies for development of continuous shared health care
- Intelligent methods for incresing of reliability of electrical networks
- Intelligent Models, Algorithms, Methods and Tools for the Semantic Web (realization)
- Mathematical modelling of air quality with applications in management of emergencies
- Modelling and simulation of complex technical problems: effective numerical algorithms and parallel implementation using new information technology
- Scientific-information gate for informatics and cybernetics.

- Approximation and Learning of Multivariable Functions by Neural Networks and Kernel Methods
- Complex investigation of biomechanical coditions of the artificial skeletal replacements applications, evaluatin of their failure reasons and proposal of conditions for increasing their stability in t
- Formal Concept Analysis of Indeterminate and Large Data: Theory, Methods and Applications
- Formal Theories of Mathematical Structures with Vagueness
- New Methods and Tools for Knowledge Discovery in Databases
- New Trends in Research and Application of Voice Technology

- Automated model building for fuzzy logic
- Methods of number theory
- New results in testing the goodness-of-fit based in Pearson-type statistics
- Quantification of cardiovascular interactions in health and disease

- Analysis of system aliances function reliability
- Autonomous computational agents
- Consortial Approach to the Development of Experimental Models
- COSTRetional Structures in Data Mining nad Discovery Science
- Krylov subspace methods - mathematical theory, stopping criteria and behaviour in finite precision arithmetic
- Special classes of matrices

- Air Quality Data Assimilation in Regional Chemistry Transport Models
- BARRANDE - E-Learning a E-Business: Auto-Adapting Web Sites via Neural Networks
- Center for Applied Cybernetics
- International cooperation in ATLAS Detector in CERN
- Mathematical foundations of inference under vagueness uncertainty
- Mathematical Theory of Iterative Processes with Applications
- Modeling the rainfall-runoff relationships by artificial intelligence methods
- Nonlinear Approximation with Variable Basis and Neural Networks
- Specialized Computational Models in Contemporary Computer Science
- Study of Dynamical Models of Pain During the Development
- Voice Technologies a Support of Information Society

- Algebraic, analytic and combinatorial methods of number theory
- General Asymptotic Theory of M-estimators
- Learning Algorithms for Local Unit Neural Networks
- Linear Optimization Problems with Inexact Data
- Research of Neural Networks Capability to Provide Nonlinear Boolean Factor Analysis
- Scalable Sparse Linear Algebraic Solvers: Analysis, Development, Implementation and Application

- Alternative learning procedures for feedforward neural networks
- Alternative mathematical models for uncertainty quantification and processing
- Analysis of reliability of large hybrid technical and biological systems
- NEUROINFORMATICS: Computational Theory of Neural Networks
- Parallelization of computer processing
- Polynomial and structured matrices
- Prediction of epileptic seizures: Extracting information with predictive power from scalp EEG by using nonlinear dynamical methods
- SOFA - Software Appliances
- SOFT COMPUTING: Theoretical Foundations and Experiments
- Toxic oxygen products and antioxidant eye protextion. Conditions leading to the exidative eye damage, its prevention or healing
- 2000 ADBIS-DASFAA Symposium on Advances in Databases and Information Systems

- MGT - Medical Guideline Technology: representing, interpreting and sharing cost-effective standards
- Nonlinear approximation by neural networks
- Parameter spaces and learning complexity of neural networks
- Study of behaviour of neurons in normal states and in the pain by methods of chaodynamics - experimental and theoretical approach

- Computational Models and Complexity of Computation
- The structure and dynamics of relationship between the psychological profile and embodiment of students of medicine

- Analysis of Informational and Dynamical Capatibilities of Recurrent Neural Networks
- Extensions of linear-algebraic problems
- Inconsistency resolution methods in the integration of data and knowledge bases
- Preconditioned Iterative Methods for Linear Algebraic

- Application of Neural Nets for Triggering of Events in Elementary Particle Physics, principal investigator
- Approximation of functions and neural networks learning algorithms
- Complexity of Continuous Models of Neurocomputing
- Development of the psychological method of newborn behavior assessment
- Information Technologies Education and Training IT EDUCTA
- Mathematical foundations of inference under vagueness and uncertainty
- Mathematical modelling of the transport and the reactions of the chemical substances in the contaminated underground water
- Research in application of the object paradigm in distributed systems

- New methods of prediction and optimization for applications in electric power network of the Czech republic

- Analysis of Informational Capabilities of a Class of Artificial Neural Networks to Optimize their Structure
- Application of modern mathematical methods in economic information processing
- Design of Modular Artificial Neural Networks
- Information Retrieval from Textual Databases Bsed on AT and NN Methodology
- New Approaches to Neural Networks in Digital Signal Processing for Applications to System Identification and Modelling
- Numerical Methods for Linear Algebraic Systems with Application to Nonlinear Problems
- Structured matrices

- Approximation of functions and architectures of neural networks
- Construction of methods for data analysis in epidemiological studies, detection of risk factors and disease risk modelling
- Hadron interaction in TeV region and their fast triggering for the quark-physics
- Research of optimization methods and develop of an interactiove system for universal functional optimization

- Non-numerical uncerianty quantification and processing in computer-aided systems for conclution drawing and decision making
- Research of optimization methods and developmentof an interactive system for univerzal functional optimization
- The approximation capabilities of multilayer neural networks

- Convergence and stability of conjugate gradient type methods for solving linear systems and computing eigenvalues in finite precision arithmetic
- Model search techniques
- The analysis and applications of new neural networks architectures

- Mathematical foundations of inference in expert systems
- Neural Nets with Neurons of Limited Number of Synapses
- The Analysis of the Generalization Abilities of Layered Neural Networks Used for Signal Processing