Nerea Urrestilla

Papers

Total Citations

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About

Nerea Urrestilla’s research sits at the intersection of cognitive neuroscience, human-robot interaction (HRI), and multimodal data analysis, with a focus on understanding how humans think and feel when interacting with intelligent systems. Her most-cited work, “Measuring Cognitive Load: Heart-rate Variability and Pupillometry Assessment” (2020, 16 citations), provides a foundational framework for using physiological signals—specifically heart-rate variability and pupil dilation—to objectively quantify cognitive load. This contribution is critical for designing adaptive robots and interfaces that can respond to a user’s mental state in real time, a key challenge in human factors engineering. Urrestilla also co-organized the 3rd Workshop on Modeling Socio-Emotional and Cognitive Processes from Multimodal Data in the Wild (2021), bridging the HCI and HRI communities to tackle the messy, real-world conditions under which intelligent systems must operate. Her work is notable for its practical, interdisciplinary approach: by blending rigorous psychophysiological measurement with the demands of “in the wild” deployment, she helps pave the way for robots and computers that can truly understand and adapt to their human partners. For students and researchers, Urrestilla’s research offers a compelling model of how to ground complex cognitive concepts in measurable, real-world data.