Pavel Osinenko, an associate professor of the Skoltech's Digital Engineering Center, is an expert in advanced control, automation, and reinforcement learning.
He holds a diploma with honors from Bauman Moscow State Technical University (2009), a PhD degree from Dresden University of Technology, Germany (2014), and a habilitation degree from Chemnitz University of Technology, Germany (2025).
Pavel's research contributions range from foundational aspects of control and dynamic system theory to reinforcement learning with guarantees, and are highlighted in top-10% Scimago ranking journals, such as IEEE Transactions on Automatic Control, IEEE Letters on Systems and Control, IEEE/CAA Automatica Sinica, Neurocomputing, Journal of Intelligent Manufacturing.
Throughout his career, Pavel worked on and supervised a number of R&D projects devoted to development of robotic and autonomous systems, digital agriculture, automation and applied computer vision.
He also developed and led the development of software frameworks for rapid prototyping and designing reinforcement learning agents, such as Regelum.
Pavel's central research direction is reinforcement learning with guarantees where he combines advanced automatic control techniques with dynamic AI.
At Skoltech, Pavel has been leading the AI in Dynamic Action (AIDA) research group.