Matej Kristan
Papers
11
Total Citations
200
H-Index
8
About
Matej Kristan is a leading researcher in autonomous robotics and interactive machine learning, with a focus on enabling robots to understand and navigate human environments. His work centers on developing systems that combine visual perception, spatial reasoning, and human-robot dialogue for continuous, lifelong learning. Kristan’s key contributions include pioneering the concept of *self-understanding*—explicitly representing what a robot knows and does not know to guide its own development—a framework detailed in his highly cited 2010 paper (38 citations). He has also advanced practical robot cognition through novel hierarchical representations of space, enabling robust room categorization (e.g., distinguishing living rooms from bathrooms) for household service robots, as demonstrated in his 2016 work (21 citations). His integrated systems for interactive learning, where robots acquire visual concepts through natural dialogue with a tutor (33 citations), have been particularly influential. With a portfolio of papers accumulating hundreds of citations, Kristan’s research bridges foundational theory and real-world application, notably in cooperative multi-robot teams and vision systems for dynamic environments like soccer robotics. His work remains essential reading for students and researchers building autonomous agents that learn and adapt in human spaces.
Research Focus
Key Achievements
Top Papers
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- 3A system for interactive learning in dialogue with a tutor33 citations · 2011
- 4Part-based room categorization for household service robots21 citations · 2016
- 5Room classification using a hierarchical representation of space18 citations · 2012
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- 8A system for interactive learning in dialogue with a tutor9 citations · 2011
- 9Room Categorization Based on a Hierarchical Representation of Space7 citations · 2013
- 10Hierarchical spatial model for 2D range data based room categorization5 citations · 2016