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Update Jan Peters information and bio
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jank324 committed Sep 12, 2024
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Expand Up @@ -17,7 +17,8 @@ We are looking forward to welcoming you to Hamburg in 2025!
We have a very exciting line-up of keynote speakers, and are very much looking forward to their talks!

{{< speaker name="Jan Peters" position="Professor for Intelligent Autonomous Systems" institute="TU Darmstadt" image="people/jan_peters.jpg" link="https://www.ias.informatik.tu-darmstadt.de/Member/JanPeters" >}}
Jan Peters is a professor at the Technical University of Darmstadt, Germany, and a researcher at the Max Planck Institute for Intelligent Systems. He has significantly advanced the understanding of machine learning, particularly in the area of robot learning and control. His work has focused on enabling robots to acquire new skills autonomously, leveraging techniques such as reinforcement learning and imitation learning. With a background in both engineering and computer science, Jan Peters has published extensively, earning recognition for his innovative approaches to making robots more adaptive and intelligent in dynamic environments. His influence extends through academia and industry, where his research has led to practical applications in robotics, enhancing the capabilities of intelligent systems across various sectors.
Jan Peters is a professor of Intelligent Autonomous Systems at Technische Universität Darmstadt and head of the Department of Systems AI for Robot Learning at the German Research Centre for Artificial Intelligence.
Having received diplomas in computer science and electrical engineering from University of Hagen and TU München, as well as an M.Sc. in Computer Science with a focus on Machine Learning and an M.Sc. in Aerospace and Mechanical Engineering with a major in nonlinear dynamics from the University of Southern California, Jan Peters earned his Ph.D. in computer science from the University of Southern California in 2007. Recognised with numerous awards, his work focuses on autonomous robotics using machine learning methods such as reinforcement learning, teaching robots human motor skills, such as juggling, table tennis, grasping and locomotion through computational models of learning and control.
{{< /speaker >}}

{{< speaker name="TBD" position="Role" institute="Institute" image="img/cheetah_outlook_slide_wide.png" link="https://github.com/desy-ml/cheetah" >}}
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