Evan Stanish
Papers
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1
H-Index
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About
Evan Stanish is a researcher at the forefront of Human-Robot Interaction (HRI), specializing in the development of predictive models for natural, intuitive robot behavior in public spaces. His primary research focuses on understanding and anticipating human intent, a critical challenge for deploying robots in crowded, unstructured environments. Stanish’s major contribution is the creation of the **People Approaching Robots Database (PAR-D)**, a pioneering collection of datasets designed to benchmark and advance intent-prediction algorithms. This work, detailed in his 2024 paper "Predicting Human Intent to Interact with a Public Robot," provides the foundational infrastructure for researchers to train and evaluate models that enable robots to recognize when a person wishes to engage, rather than simply passing by. By addressing this subtle but vital social cue, Stanish’s research directly impacts the safety, efficiency, and social acceptance of service robots in settings like malls, airports, and hospitals. His work is gaining traction as a key resource in the field, offering a standardized framework for one of HRI’s most pressing problems. Stanish’s contributions are essential reading for anyone exploring the future of autonomous, socially-aware robotics.
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Top Papers
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