Pavel Osinenko studied control engineering at the Bauman Moscow State Technical University from 2003 through 2009. He started his postgraduate education in vehicle control systems at the same university. In 2011, Pavel moved to the Dresden University of Technology after receiving a Presidential Grant. He obtained a PhD degree in 2014 with a dissertation on vehicle optimal control and identification.
Pavel has work experience in the German private sector and at the Fraunhofer Institute for Transportation and Infrastructure Systems.
In 2016, he made a transition to the Chemnitz University of Technology as a group leader and research coordinator. He was actively involved in project coordination, doctorate supervision, teaching, administration etc.
Pavel’s major focus of research has been on reinforcement learning, especially its safety, and computational aspects of dynamical systems.
Currently, he addresses the connections between control theory and machine learning, and, in particular, the matters of meeting specified certificates on reinforcement learning methods in dynamical context.