Have been interested in science & technology since childhood.
Attended and won multiple international science competitions during high school including the International Olympiad in Astronomy and Astrophysics (silver and gold medals) and Intel ISEF (3rd place).
Studied physics at Imperial College London which consistently gets among the world's top-10-ranked universities. Got involved in data analysis within the LHCb and later ATLAS collaborations at CERN.
Worked as a data scientist in e-commerce preparing predictive models, performance analyses, simulations etc.
Launched own startup focusing on real-time processing of e-commerce data. Designed and developed the entire data-processing pipeline and ML models.
Worked as an ML engineer in a tech company focusing on document image processing, classification and OCR.
Currently a member of the modelling team at Makers working on a new approach to simulations of distributed energy resources.
Anglický jazykMichal Racko
The currently ongoing large-scale adoption of distributed energy resources such as photovoltaic arrays, batteries, fuel cells and others has brought about a significant room for improvements in both cost and energy savings. The supply-demand nature of the power grid further increases the potential for energy-bill reduction. Robust simulations of DERs and their relationships are a paramount for any optimization effort.
We developed a framework which simplifies the simulation work and provides a useful abstraction for complex systems. An example simulation of a model city transmission grid will be presented.