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About

Jasmin Steinwender is a researcher specializing in cooperative human-robot interaction (HRI), with a particular focus on enabling robots to communicate, learn, and collaborate with humans in natural and adaptive ways. Her work sits at the intersection of robotics, cognitive science, and artificial intelligence, addressing some of the most fundamental challenges in building robots that can function as genuine cooperative partners. Among her most significant contributions is her research on referential grounding and ambiguity resolution — developing strategies that allow robots to identify objects and resolve unclear situations using perspective-taking and multimodal communication. Her highly cited 2010 paper on grounding referents (73 citations) demonstrates how efficient dialogue can guide robots in identifying specific objects during interaction. Steinwender also made substantial contributions to the CHRIS project, a platform-independent cooperative HRI architecture, advancing robot capabilities in action learning, imitation, shared planning, and communication through gaze and speech (collectively accumulating over 100 citations). Her involvement in developing the BERT2 robotic infrastructure at Bristol Robotics Laboratory further highlights her systems-level expertise. Across her body of work, Steinwender has helped lay important groundwork for robots that can observe, learn, and meaningfully collaborate with naïve human users — a critical step toward real-world human-robot cooperation.