Mathematics was one of the first fields that started receiving support from the Neuron Fund. After all, Karel Janeček, Neuron's founder and benefactor, is also a mathematician.
The 2014 Neuron Grants will be presented on 11 December 2014. Visit our website or subscribe to our newsletter and get regular updates on the Neuron Grants gala ceremony.
Each year, one research project in mathematics receives a grant of up to CZK 1 million for three years. The Neuron Fund for the Support of Science provides financial backing to selected outstanding Czech mathematicians, allowing them to pursue their research and find solutions that could have significant implications for the entire field of mathematics.
Doc. Mgr. Michal Koucký, Ph.D. – Lower Bounds for Dynamic Data Structures
Dynamic data structures are one of the basic research areas in theoretical computer science. This project aims to prove polynomial lower bound estimates for dynamic data structures. Thanks to this grant, Koucký is able to continue exploring his theory that will indicate whether a particular maths problem can at all be effectively solved. His research will advance our current knowledge in theoretical computer science.
RNDr. Jan Kalina, Ph.D. – Robust Analysis of High-Dimensional Data
The aim of the project is to devise new statistical methods suitable for the analysis of high-dimensional data. These classification methods are robust (resistant) to noise and remote data observation. Kalina's research will lead to a more precise analysis of gene expression in patients in order predict the risk of heart attack.
RNDr. Miroslav Bulíček, Ph.D. – Qualitative Analysis of Incompressible Navier-Stokes-Fourier Equations
The project focuses on the mathematical analysis of evolution incompressible Navier-Stokes-Fourier equations in two and three dimensions. The main objective of the project revolves around the smoothness of weak solutions of the system, i.e., to prove the existence of traditional solution or the maximum regularity for a given problem.
Mgr. Robert Šámal, Ph.D. – Semidefinite Programming and a Graph Theory
This project studies graph parameters defined by semidefinite programming. Some of these parameters were previously used as a tool to approximate traditional parameters. The aim is to explore these graph parameters, their quantitative and qualitative features within the context of graph theory. The project follows up on the results obtained by leading international mathematicians and computer scientists in the last fifteen years. The objective is to expand on these results in a direction that has so far been overlooked. This project should improve theoretical understanding of semidefinite input parameters and the practical knowledge of values for specific graphs and also to create an effective combinatorial algorithm for the calculation of these values.