Karl Granström

Karl Granström is a Postdoc in the Signal Processing group. Before starting at Chalmers he was a Postdoc at the University of Connecticut, where he worked together with Peter Willett and Yaakov Bar-Shalom. Karl received his PhD degree in Automatic Control in November 2012, and the Master of Science degree in Applied Physics and Electrical Engineering in May 2008, both from Linköping University. His research interests are within the fields of sensor fusion, robotics and machine learning. Karl has also contributed actively to the tracking literature for almost a decade, especially papers about extended object tracking. He has won multiple conference paper awards, and in 2018 he was awarded the ISIF Young Investigator Award by the International Society of Information Fusion (ISAF) for his research contributions and his service to the community.

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Multi-Object Tracking for Automotive Systems (edX) EdX
Chalmers University of Technology,ChalmersX

Multi-Object Tracking for Automotive Systems (edX)

Discover the critical skill of Multi-Object Tracking (MOT) as you learn how to accurately localize and track dynamic objects within complex environments, particularly relevant for advancing autonomous vehicles' safety and efficiency. This course provides a thorough grounding in the principles and applications of MOT in automotive systems, empowering you with the knowledge to contribute significantly to this rapidly evolving field.

Self Paced
Self-Paced
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