Lars Kunze

Postdoctoral Research Assistant

Oxford Robotics Institute, Department of Engineering Science, University of Oxfordd

Stipendiary Lecturer in Computer Science

Keble College

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About Me

Lars is a Postdoctoral Research Assistant in Mobile Robotics with the Oxford Robotics Institute, within the Department of Engineering Science, University of Oxford, Oxford, U.K., and a Stipendiary Lecturer of Computer Science with Keble College, Oxford, U.K.

His research concerns the design and development of fundamental AI techniques for autonomous robot systems that operate in complex, real-world environments. In particular, he focuses on semantic scene understanding using logical as well as statistical-relational models. Within the Oxford Robotics Institute, he works on transparent and interpretable models that can provide detailed explanations in the context of autonomous driving.

Lars studied Cognitive Science (BSc, 2006) and Computer Science (MSc, 2008) at the University of Osnabrück, Germany, and partly at the University of Edinburgh, UK. He received his PhD (Dr. rer. nat.) from the Technical University of Munich, Germany, in 2014.

During his PhD, Lars worked on methods for naive physics and commonsense reasoning in the context of everyday robot manipulation. He contributed to several national, European and international projects including RoboHow, RoboEarth, and the PR2 Beta program.

In May 2013, Lars was appointed as a Research Fellow in the Intelligent Robotics Lab at the School of Computer Science at Birmingham University. Here he worked on qualitative spatio-temporal models for perception planning and knowledge-enabled perception, contributing to the European research projects STRANDS and ALOOF.

He was a visiting researcher in the JSK Lab at the University of Tokyo, Japan (Summer 2011) and the Human-Robot Interaction Laboratory at Tufts University, US (Spring 2015).

Research Interests

  • Artificial Intelligence
  • Robotics
  • Scene Understanding
  • Knowledge-enabled Perception
  • Perception Planning
  • Knowledge Representation and Reasoning
  • Human-robot Interaction
  • Long-term Autonomy