Ing. Miroslav Čepek, Ph.D.

2023 - 2025

The EDIH CTU represents a major European Digital Innovation Hub in the Czech Republic in the field of Artificial Intelligence (AI) and Machine Learning (ML) transferring trustworthy solutions and services to the industry, health, transportation and energy sectors. The EDIH CTU, with its vision "Inspire & Make the Czech AI-driven Industry", aims to become the innovation and technology leader in providing professional AI/ML services for the local SMEs, small mid-caps and public sector organizations with respect to their digital and green transformation. The strong consortium partners representing academia, business sector and key associations of enterprises in the Czech Republic provide sufficient know-how, expertise and state-of-the-art experimental facilities to serve the needs of the public and private sector at the national and also international level. The major focus is on promoting digital transformation adoption, providing high-quality services, education and knowledge sharing, pursuing ecosystem development, and establishing strong inter-EDIH collaboration. The consortium builds upon already existing partnerships in AI and manufacturing enabling best practice sharing, expertise exchange, and joint activities seeking far-reaching synergies thus strengthening the far-reaching impacts of the European network of EDIHs.

2024 - 2027

The FOCAL project aims to advance our understanding of complex Earth systems and mitigate climate change impacts through five main objectives: developing a high-performance computing platform for better climate and earth system modelling; creating AI modules for efficient climate data exploration; designing web-apps to support decision-making; conducting pilot studies to address assessment challenges and demonstrate app benefits; and fostering a collaborative network across research, data providers, data science, and HPC infrastructure. By combining expertise and integrating data from multiple sources, FOCAL aims to improve climate models, inform policy decisions, and support sustainable development.

2024 - 2026

PoliRuralPlus

2010 - 2011

Goal of this project is to extend extisting part for data preprocessing in the FAKE GAME project. In this project we will look for and implement selected methods for data preprocessing, namely in the field of text mining of the czech texts, preparation of time series data for data mining and feature extraction. We will also implement methods for feature selection and feature ranking as well as extensions of current methods. In this field we will first implement well known algorithms and then we will search for new algorithms. We will implement selected data preprocessing methods in another, well konwn, data mining tools (Kettle and IBM SPSS Modeler). And we will compare results of our methods to methods present in those tools. The next goal of this project is to improve exiting implementation of Automatic Data Preprocessing Algorithm. This algorithm automaticaly selects data preprocessing methods in order to achieve the highest accuracy of the model. This algorithm utilizes genetic al