prof. Jan Platoš, Ph.D.

Professional Background

Researcher and professor at VSB - Technical University of Ostrava, specializing in machine learning, data mining, and adaptive algorithms. His work focuses on building intelligent systems that can learn from continuously evolving data, with an emphasis on handling data streams, concept drift, and changing environments. He explores how models can remain accurate and efficient over time without requiring frequent manual updates, especially in real-time or large-scale applications.

In addition to adaptive learning, his research includes nature-inspired optimization methods, such as evolutionary and swarm-based algorithms, which are used to improve tasks like feature selection, clustering, and model tuning. He applies these methods across a range of domains, including time series forecasting, sentiment analysis, misinformation detection, and image classification. His work bridges theory and practice, often combining lightweight models with scalable solutions that can be deployed in dynamic or data-intensive environments.

With a strong interest in practical AI, he collaborates on interdisciplinary projects and regularly contributes to applied research in areas such as energy systems, smart grids, and digital media. His overarching goal is to design machine learning approaches that are not only theoretically sound but also robust, interpretable, and adaptable to real-world conditions.