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Institute of Computer Science
The Czech Academy of Sciences
The Czech Academy of Sciences
"The question of whether Machines Can Think... is about as relevant as the question of whether Submarines Can Swim." - E. W. Dijkstra
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 logicSupervisor:
- Mathematical fuzzy logicSupervisor:
- Logic and reasoningSupervisor:
- Algorithmic problems in substructural logicsSupervisor:
- Modal and substructural logics: reasoning about dynamic behaviour in computational and social contextSupervisor:
- Embedding large structures in graphsSupervisor:
- Packing using randomized algorithmsSupervisor:
- Complexity measures in neural networksSupervisor:
Machine Learning
- Analysis of data-mining methods based on one-to-one neural networksSupervisor:
- Estimates of the Number of Patterns in the PAC Model for Nonconsistent SeparationSupervisor:
- Robust classification for high-dimensional dataSupervisor:
- Robust estimation for neural networksSupervisor:
- Comparisons of abilities of shallow and deep networksSupervisor:
- Robustness of neural network learningSupervisor:
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 analysisSupervisor:
- Brain computer interfaceSupervisor:
- Research and comparison of methods of group factor analysis for fMRI dataSupervisor:
Complex Systems
- Interactions in complex systems and their detection in time seriesSupervisor:
- Distinguishing true and spurious cross-frequency coupling in brain dynamicsSupervisor:
- Brain Activity ModellingSupervisor:
- Methods for complex system analysisSupervisor:
- Analysis of complex systems using methods of complex networksSupervisor:
- Graph theoretic properties of complex networks and their modelsSupervisor:
- Satellite data for environmental modeling (diploma thesis)Supervisor:
- Metody redukce dat v environmentálnách systémechSupervisor:
- Weather and air quality modeling and forecasting - Mathematical and statistical methods for data assimilation in complex dynamical systemsSupervisor:
Statistical modelling
- Statistical methods for longitudinal and response-time data in educational, psychological and health-related measurementsSupervisor:
- Computational psychometricsSupervisor:
- Survival analysis of multivariate censored dataSupervisor:
- Statistical methods for dimensionality reduction and classification for multivariate data with applications in biomedicine.Supervisor:
- Modern semiparametric methods and their application to modeling and evaluation of meteorological and environmental fieldsSupervisor:
Formal Verification
- Software SynthesisSupervisor:
- Constraint SolvingSupervisor:
- Verification of Complex SystemsSupervisor:
CONTACT
Pod Vodárenskou věží 271/2
182 00 Praha 8
Phone (+420) 266 052 083
E-mail: ics@cs.cas.cz
