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About

Jessica Merino is a researcher whose work sits at the compelling intersection of human-robot interaction, assistive robotics, and intelligent environments. Her scholarship focuses on developing intuitive interfaces that enable humans to communicate with and direct robotic systems, with a particular emphasis on supporting aging-in-place and post-stroke rehabilitation. Merino's most influential contribution, "A Gesture Learning Interface for Simulated Robot Path Shaping With a Human Teacher" (2014, 37 citations), demonstrates her commitment to making robotic systems accessible through natural human movement, a theme she reinforced in her earlier Kinect-based gesture recognition work (2012, 23 citations), which leverages depth-sensing technology and Growing Neural Gas algorithms. Her development of the Assistive Robotic Table (ART) — explored across multiple publications and garnering 19 citations — exemplifies her translational approach, bringing laboratory concepts into clinical rehabilitation settings through rigorous participatory design with healthcare professionals. Merino has also contributed forward-thinking conceptual frameworks, including visions of patient rooms as architectural-robotic ecosystems and sensor-embedded smart homes. Collectively, her work advances a future where intelligent, responsive environments meaningfully improve quality of life for vulnerable populations.