Quantum Information, (Quantum) Machine Learning, Earth Observations
Dr Tomasz Rybotycki has 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 estimation 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”.
Since 2017, dr Rybotycki works in the Systems Research Institute of the Polish Academy of Sciences as a research assistant.
In 2020, dr Rybotycki obtained Research Scholarship at AstroCeNT, where he investigated the use of metaheuristics for quantum neural networks training. The same year he started working at 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 again in 2023. Currently he works on Quantum Machine Learning with prof. Piotr Gawron. His research focuses on quantum circuits optimization using ZX calculus and applying (Q)ML techniques for earth observation.
Postdoc at Scientific Computing & Information Technology Group
tryb at camk.edu.pl