Parham Nooralishahi

Papers

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About

Parham Nooralishahi is a researcher whose work sits at the compelling intersection of human-robot interaction, affective computing, and trust modeling. His primary research explores how we can objectively measure and model human trust in autonomous systems—a critical challenge for the future of collaborative robotics. His most cited work, "Exploring Psycho-Physiological Correlates to Trust" (2016, 31 citations), introduces a novel methodology that bridges subjective psychological measures with objective physiological signals, such as heart rate and skin conductance, to capture trust in real-world, natural dialog scenarios. By embedding fifteen subjective measures into realistic interactions, Nooralishahi provides a robust framework for moving beyond self-reported trust toward a more holistic, data-driven understanding. This foundational contribution is essential for developing adaptive robots that can sense and respond to human trust levels in real time. His research not only advances theoretical models of human-machine trust but also has direct implications for designing safer, more intuitive autonomous systems in fields ranging from manufacturing to healthcare.