Research Group
Martin Výboh
Research areas: time-series, machine learning, prediction methods, energy
Position: Research Engineer
Martin is a research engineer at KInIT specialising in predictive modelling and optimisation. As a member of the Green and Secure Environment team, he used advanced time-series forecasting, machine learning, and probabilistic modelling to address challenges in domains such as energy markets, EV charging, mobility, and heating. Martin actively explores intersections between research and industry partnerships. A graduate of Comenius University with a Master’s in Probability and Mathematical Statistics, Martin was awarded the Dean’s Award (2024) for his studies and thesis on high-dimensional data visualisation.
Selected Projects
Selected Publications
Fully differentiable Lagrangian convolutional neural network for physics-informed precipitation nowcasting
Pavlík, P., Výboh, M., Bou Ezzedine, A., Rozinajová, V. This paper presents a convolutional neural network model for precipitation nowcasting that combines data-driven learning with physics-informed domain knowledge. We propose…