Oskars Teikmanis joined EDI in September 2021 and became a researcher in July 2023. He received his B. Sc. degree in Engineering Science from the Technical University of Munich (TUM) in 2016. He continued his studies at TUM to obtain an M. Sc. degree in Mechatronics and Information Technology in 2019, completing his master’s thesis in robot localization at the German Aerospace Center (DLR). After having worked in the field of autonomous driving in Munich for several years, Oskars moved to Latvia.
His current research interests include the application of differentiable physics simulators for gradient-based control policy learning, and simulation-to-reality strategies for transferring such policies to physical robots.
Related publications:
Recent projects
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Smart Materials, Photonics, Technologies, and Engineering Ecosystem (MOTE) #VPP
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Artificial Intelligence in Manufacturing leading to Sustainability and Industry 5.0 (AIMS5.0) #ChipsJU
Recent publications
- Oskars Teikmanis, Aleksandrs Levinskis, Andris Ivars Mackus, Artis Rušiņš, Amr Elkenawy, Marta Tropa, Modris Greitans. 2023. "Automated Vehicle Platform with Connected Driving Capabilities 2023 IEEE International Conference on Intelligent Transportation Systems (ITSC)"
- Kārlis Freivalds, Laura Leja, Oskars Teikmanis, "Learning to Move Objects with Fluid Streams in a Differentiable Simulation", ROBOT 2024 7th Iberian Robotics Conference, IEEE,
- Laura Leja, Oskars Teikmanis, Kārlis Freivalds, 2024. "Shaping Flames with Differentiable Physics Simulations" "Machine Learning and the Physical Sciences" , NeurIPS 2024
- Kārlis Freivalds, Oskars Teikmanis, Laura Leja, Rodions Saltanovs, Ralfs Āboliņš, "Learning Fluid-Directed Rigid Body Control", "Machine Learning and the Physical Sciences" at NeurIPS 2024
- Kārlis Freivalds, Laura Leja, Oskars Teikmanis. 2024. Learning to Move Objects With Fluid Streams in a Differentiable Simulation. https://www.scopus.com/pages/publications/85216016801?origin=resultslist