Tomasz Rybotycki

Dr Tomasz Rybotycki obtained his Ph.D. in 2023 from the Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland. His doctoral advisor was Prof. Piotr Kulczycki.

During his Ph.D., dr Rybotycki worked on the predictive estimation of the density of non-stationary data streams, where he designed a kernel density estimator-based algorithm for predictive analysis of data density. The title of his thesis was “Estimation of data density for non-stationary streaming data”. During his Ph.D. he also obtained a B.Sc. degree in Physics, after successfully defending his B.Sc. thesis entitled “Framework for performing experiments on IBM Quantum Computers”. Starting in 2017, dr Rybotycki is working as a Research Assistant at the Systems Research Institute of the Polish Academy of Sciences.

In 2020, dr Rybotycki obtained a Research Scholarship at AstroCeNT, where he investigated using metaheuristics for quantum neural network training. The same year he started working at the Centre for Theoretical Physics of the Polish Academy of Sciences, initially as a researcher/software engineer, and later as a (theoretical physics) Ph.D. student in a project. He left the Centre for Theoretical Physics in 2022.

In 2022, dr Rybotycki started working at ACK Cyfronet AGH, where, as a senior programmer, he is responsible for preparing an auto quantum machine learning e-platform.

Dr Rybotycki joined AstroCeNT (and later NCAC) again in 2023. Currently, he works on Quantum Machine Learning with Prof. Piotr Gawron. His research focuses on quantum circuit optimization using ZX calculus and applying (Q)ML techniques for earth observation. He also explores different QML applications at CEAI AGH, as an AI Research Specialist.