Jonathan Velez
Papers
3
Total Citations
16
H-Index
2
About
Jonathan Velez is a researcher at the intersection of robotics, human-robot interaction, and assistive technology. His work centers on two critical challenges: enabling robots to understand and express social cues, and ensuring assistive robotic systems are effectively evaluated for real-world use. In his most cited work, "An interdisciplinary taxonomy of social cues and signals in the service of engineering robotic social intelligence" (2014, 11 citations), Velez laid foundational groundwork for the field of Social Signal Processing, proposing a structured taxonomy to help machines interpret human intentions through non-verbal behavior—a key step toward naturalistic human-robot interaction. He further explored this theme in "Robot Emotive Display Systems and the Analogous Physical Features of Emotion" (2016, 2 citations), investigating how robots can use physical features to convey emotion. Complementing this social focus, Velez contributed to the practical deployment of assistive technology with "Toward Developing a Framework for Standardizing the Functional Assessment and Performance Evaluation of Assistive Robotic Manipulators (ARMs)" (2015, 3 citations), addressing a critical gap in evaluating robotic aids for individuals with disabilities. His interdisciplinary approach—bridging cognitive science, engineering, and human factors—positions him as a thoughtful contributor to making robots both more socially intelligent and more practically useful.
Research Focus
Key Achievements
Top Papers
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