Stefan Schaal
Stefan Schaal is a robotics researcher whose work has focused on motor control and learning. He studied mechanical engineering at the Technical University of Munich, worked as a postdoctoral fellow at MIT's Artificial Intelligence Lab, and built a robotics lab in Japan. In 1997 he joined the faculty of the University of Southern California, where he rose to full professor. He helped found the Max Planck Institute for Intelligent Systems in 2009 and was elected an IEEE Fellow in 2013. In 2018 he joined Google X to lead a robotics research team, and in September 2025 he co-authored RoboBallet, a paper on planning for multi-robot reaching.
Timeline
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1987
A mechanical engineering diploma
He graduates in mechanical engineering from the Technical University of Munich in 1987.
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1991–1994
A postdoctoral fellowship at MIT
From 1991 to 1994, he works as a postdoctoral fellow at MIT's Artificial Intelligence Lab.
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1992
A robotics lab in Japan
In 1992 he becomes an invited researcher at ATR in Japan, where he creates a robotics lab focused on biological principles of motor control and learning.
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1997
A professor at USC
At the University of Southern California, he joins the faculty in 1997 and advances to full professor.
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2009
Founding the Max Planck institute
In 2009 he becomes a key founder of the Max Planck Institute for Intelligent Systems.
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2013
An IEEE Fellow
He is elected an IEEE Fellow in 2013.
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2018
A robotics team at Google X
In 2018 he joins Google X to lead a robotics research team.
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September 2025
A multi-robot reaching paper
In September 2025 he co-authors RoboBallet, a paper on planning for multi-robot reaching with graph neural networks and reinforcement learning.
Sources and credits
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- Stefan Schaal – Computer Scientist in Robotics, Artificial Intelligence, and Autonomous Systems
- Oral-History:Stefan Schaal
- Stefan Schaal - Wikipedia
- Computational Learning and Motor Control Lab | Main / Stefan Schaal
- Robot Learning: Towards Real World Applications | Contextual Robotics Institute
- [2509.05397v1] RoboBallet: Planning for Multi-Robot Reaching with Graph Neural Networks and Reinforcement Learning