Maia Stiber
Papers
10
Total Citations
129
H-Index
6
About
Maia Stiber is a human-robot interaction (HRI) researcher whose work centers on robot error detection, error management, and the design of more intuitive collaborative robotic systems. Her research addresses one of the field's most pressing challenges: how robots can recognize and recover from their own mistakes by interpreting natural human social signals, rather than relying on rigid, task-specific programming. In her most-cited works — each garnering 28 citations — she demonstrated that human responses to robot errors vary meaningfully by severity and context, and that these signals can be leveraged to build more adaptive, trust-preserving systems. Her 2021 work on user-centric programming aids for kinesthetic robot teaching (22 citations) extends this human-centered philosophy to the design of accessible robot training tools. More recently, Stiber has pushed these ideas into multimodal and conversational robotics, co-organizing the ERR@HRI challenge series and exploring LLM-driven facial expression generation for socially responsive robots. With over 120 total citations across a focused body of work, her research consistently advances the vision of robots that are not only capable collaborators but also graceful, self-aware partners in everyday human environments.
Research Focus
Key Achievements
Top Papers
- 1Modeling Human Response to Robot Errors for Timely Error Detection28 citations · 2022
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- 3On Using Social Signals to Enable Flexible Error-Aware HRI23 citations · 2023
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- 7Forging Productive Human-Robot Partnerships Through Task Training6 citations · 2023
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