Jennifer Sorinas

Papers

Total Citations

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About

Jennifer Sorinas is a researcher whose work lies at the intersection of affective computing and human-robot interaction (HRI), with a particular focus on the physiological underpinnings of emotional engagement. Her most-cited study, "Exploring the Physiological Basis of Emotional HRI Using a BCI Interface" (2017), pioneered the integration of brain-computer interface (BCI) technology to decode emotional states during human-robot encounters. By analyzing neural and physiological signals, Sorinas demonstrated how robots can adapt their behavior in real-time to user affect, laying groundwork for more empathetic and responsive autonomous systems. Though her citation count is modest, this foundational paper has informed subsequent work in socially assistive robotics and closed-loop BCI systems. Sorinas’s contribution is notable for bridging cognitive neuroscience and engineering, offering a rigorous, data-driven method to quantify emotional experience in HRI. Her research holds promise for applications in therapeutic robotics, where understanding user affect is critical. For students and researchers entering this interdisciplinary field, Sorinas exemplifies how targeted, methodologically sound studies can shape emerging paradigms in human-centered robotics.