Selected Topics

Institute of Computer Science AS CR is a public research organization, which, according to its founding charter does not have a doctoral degree program. The Institute focuses on basic research, however, employs PhD students and post-docs in the areas covered by the research institute.

Theoretical Computer Science

Abstract algebraic logic
Supervisor: doc. Ing. Petr Cintula, Ph.D., DSc.
Mathematical fuzzy logic
Supervisor: doc. Ing. Petr Cintula, Ph.D., DSc.
Logic and reasoning
Supervisor: doc. Ing. Petr Cintula, Ph.D., DSc.
Algorithmic problems in substructural logics
Supervisor: RNDr. Zuzana Haniková, Ph.D.
Modal and substructural logics: reasoning about dynamic behaviour in computational and social context
Supervisor: Mgr. Igor Sedlár, Ph.D., Mgr. Marta Bílková, Ph.D.
Embedding large structures in graphs
Supervisor: Mgr. Diana Piguet, Ph.D.
Packing using randomized algorithms
Supervisor: Mgr. Diana Piguet, Ph.D.
Complexity measures in neural networks
Supervisor: doc. RNDr. Jiří Šíma, DrSc.

Machine Learning

Analysis of data-mining methods based on one-to-one neural networks
Supervisor: Ing. František Hakl, CSc.
Estimates of the Number of Patterns in the PAC Model for Nonconsistent Separation
Supervisor: Ing. František Hakl, CSc.
Robust classification for high-dimensional data
Supervisor: RNDr. Jan Kalina, Ph.D.
Robust estimation for neural networks
Supervisor: RNDr. Jan Kalina, Ph.D.
Comparisons of abilities of shallow and deep networks
Supervisor: RNDr. Věra Kůrková, DrSc.
Robustness of neural network learning
Supervisor: RNDr. Věra Kůrková, DrSc.
Several recent studies revealed that some deep networks can be easily fooled by changing an image in a way imperceptible to humans which can cause a deep network to label the image as something else entirely. Thus it is important to investigate robustness of learning of networks with respect to adversarial patterns. The goal of the dissertation is to design a multiobjective algorithm generating imperceptible perturbations of images leading to their misclassifications. Evolutionary algorithms for generation of adversarial patterns will be developed that maximize the error of the model while being as similar to original training patterns as possible. The role of depth of networks and locality properties of computational units in misclassiffication will be analyzed. Methods of making machine learning models more robust to adversarial patterns will be investigated.
Boolean nonlinear factor analysis
Supervisor: Ing. Dušan Húsek, CSc.
Brain computer interface
Supervisor: Ing. Dušan Húsek, CSc.
Research and comparison of methods of group factor analysis for fMRI data
Supervisor: Ing. Dušan Húsek, CSc.

Complex Systems

Interactions in complex systems and their detection in time series
Supervisor: RNDr. Milan Paluš, DrSc.
Distinguishing true and spurious cross-frequency coupling in brain dynamics
Supervisor: RNDr. Milan Paluš, DrSc.
Brain Activity Modelling
Supervisor: Ing. Mgr. Jaroslav Hlinka, Ph.D.
Methods for complex system analysis
Supervisor: Ing. Mgr. Jaroslav Hlinka, Ph.D.
Analysis of complex systems using methods of complex networks
Supervisor: doc. Ing. David Hartman, Ph.D.
Graph theoretic properties of complex networks and their models
Supervisor: doc. Ing. David Hartman, Ph.D.
Satellite data for environmental modeling (diploma thesis)
Supervisor: PhDr. Viktor Fuglík, Ph.D.
Metody redukce dat v environmentálnách systémech
Supervisor: prof. Ing. Emil Pelikán, CSc.
Weather and air quality modeling and forecasting - Mathematical and statistical methods for data assimilation in complex dynamical systems
Supervisor: RNDr. Kryštof Eben, CSc.

Statistical modelling

Statistical methods for longitudinal and response-time data in educational, psychological and health-related measurements
Supervisor: doc. RNDr. Patrícia Martinková, Ph.D.
Computational psychometrics
Supervisor: doc. RNDr. Patrícia Martinková, Ph.D.
Survival analysis of multivariate censored data
Supervisor: doc. Mgr. Zdeněk Valenta, Ph.D.
Statistical methods for dimensionality reduction and classification for multivariate data with applications in biomedicine.
Supervisor: doc. Mgr. Zdeněk Valenta, Ph.D.
Modern semiparametric methods and their application to modeling and evaluation of meteorological and environmental fields
Supervisor: Ing. Marek Brabec, Ph.D.

Formal Verification

Software Synthesis
Supervisor: doc.Dipl.Ing. Stefan Ratschan, Dr.-tech.
Constraint Solving
Supervisor: doc.Dipl.Ing. Stefan Ratschan, Dr.-tech.
Verification of Complex Systems
Supervisor: doc.Dipl.Ing. Stefan Ratschan, Dr.-tech.