Niko Sünderhauf

Bio: Professor Niko Suenderhauf is Chief Investigator and member of the Executive Committee of the QUT Centre for Robotics (QCR) where he leads the Visual Learning and Understanding program. Between 2017 and 2020 Niko was Chief Investigator and Project Leader of the Australian Centre of Excellence for Robotic Vision (ACRV).

Niko received his PhD from Chemnitz University of Technology, Germany in 2012. In his thesis, he developed new and outlier-robust mathematical methods for robotic localisation and mapping, as well as general probabilistic estimation problems.

Niko’s research vision and expertise has been recognised by internationally competitive awards such as a Google Faculty Research Award and an Amazon Research Award.

Research Expertise: Niko conducts research in robotic vision, at the intersection of robotics, computer vision, and machine learning. His research focuses on scene understanding, SLAM, localisation, the effective combination of machine learning with classical methods, and reliable and safe machine learning in robotics.

In the context of the Hub, Niko wants to investigate with the Hub’s partners how new implicit representations can improve the efficiency and effectiveness of large-scale mapping over long time horizons; how robots can effectively combine machine learning with hand-written algorithms, demonstrations, or analytical controllers to perform complex tasks such as mobile manipulation on an underwater platform; how machine learning can be made more reliable, robust and adaptable to new situations; and how the combination of learning-based and analytical methods for control can allow us to give safety and performance guarantees.

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