InterCoML Conference – NextGen Synergy: Control Theory & Machine Learning
We are proud to announce the inaugural conference of COST Action CA24136! The NextGen Synergy: Control Theory & Machine Learning conference aims to bridge the gap between Control Theory (CT) and Machine Learning (ML), two dynamic fields that are increasingly intersecting. A broad array of topics will be discussed, including but not limited to the following: Strengthening control-theoretical […]
InterCoML Conference – NextGen Synergy: Control Theory & Machine Learning
The DYNALIFE interdisciplinary meeting will explore the role of quantum phenomena in the information processing, transfer of complex living systems, decision making and cognition as well as on methods and techniques for simulating biological informational phenomena.
The conference will feature a broad spectrum of topics at the intersection of quantum physics, biology, and information science. We invite submissions of new and original research on a variety of subjects, including but not limited to the following:
quantum transport and sensing
quantum effects in the brain, perception and cognition
role of quantum effects in the origins of life and complexity
quantum-to-classical transition in living organisms
quantum computing for molecular biology
quantum-like modelling and quantum bio inspired technologies
quantum decision making and cognition.
The conference aims to foster interdisciplinary collaboration among working groups and stimulate cross-field interactions to deepen our fundamental understanding of biological information and its role in the origin of life. Additionally, it will leverage cutting-edge biological insights to describe phenomena in cognition and decision-making and help to explore potential applications (e.g. medicine, technology).
The conference programme includes 4-5 keynote talks, 9 contributed talks, a range of poster presentations and 3 panel discussions.
Best Junior Paper Award – 2025
Congratulations to our colleagues in the Best Junior Paper Award 2025 competition. 1st place was awarded to Marko Ruman for his paper „Knowledge Transfer in Deep Reinforcement Learning via an RL-Specific GAN-Based Correspondence Function“IEEE Access, vol. 12 (2024), pp. 177204–177218 3rd place was awarded to Antonie Brožová for her paper „Spatial-temporal source term estimation using […]
Seminar: Gaussian-process-based correction of bias in atmospheric inversion
Gaussian-process-based correction of bias in atmospheric inversion Accurate estimation of atmospheric release sources and their time profiles is essential for assessing the environmental impacts of incidents such as the emission of radionuclides from forest fires in Chernobyl in 2020 or the release of ruthenium in 2017, whose source has not been officially confirmed to this […]
Expert Meeting
A representative of our department attended an expert meeting on dual-use technologies held at the Ministry of Industry and Trade on 19 November 2025. The event brought together specialists to discuss prospects for dual-use applications within the National Research and Innovation Strategy for Smart Specialisation of the Czech Republic (National RIS3 Strategy).
Interactions between Control Theory and Machine Learning (InterCoML)
This Action will exploit the deep interconnections between Control Theory (CT) and Machine Learning (ML). It will boost applications of tools from CT to ML and vice versa, and explore the great applicative potential that can be released by combining these two rapidly evolving research areas. In particular, it aims to(i) strengthen the control-theoretical foundations […]
Seminar: Towards secure Artificial Intelligence: Private distributed learning and strategic decision making
Towards secure Artificial Intelligence: Private distributed learning and strategic decision making Artificial intelligence faces security challenges at many levels, such as the exposure of sensitive data, the vulnerability of distributed learning systems, and the need to design robust policies under adversarial uncertainty, to name but a few. In this seminar, I will discuss two approaches […]
Bayesian Methods for Machine Learning
Bayesian Methods for Machine Learning The subject is focused on the practical use of basic Bayesian modelling methods in the dynamically evolving machine learning theory. In particular, it studies the construction of appropriate models providing a description of real phenomena, as well as their subsequent use, e.g., for forecasting future evolution or learning about the […]
Theory of Automatic Control
Theory of Automatic Control The course introduces the design, realization, and implementation of digital controllers in industrial practice. It focuses primarily on theoretical training in the field of digital control of linear dynamic systems in terms of stability, accuracy, and quality of transient processes in a closed control loop. Lecturer: Lenka Kuklišová Pavelková Where: […]
Statistics
Statistics The course introduces elements of mathematical statistics. Topics: descriptive statistics, elements of probability theory, discontinuous and continuous random quantities, probability function, probability density function, point and interval estimates, testing of statistical hypotheses, elements of ANOVA, linear regression, correlation analysis, time series analysis, elements of index analysis. Lecturer: Ladislav Jirsa Where: Department of Statistics and […]