BRAINS Lab

BRAINS (Bridging Robots, AI, Neuroergonomics, and Social Cognition) Lab

At the BRAINS Lab, we bridge robotics, artificial intelligence, neuroergonomics, and social cognition to advance the science of human–machine interaction.

Our mission is to design and study machines that are not only technologically capable but also effective, intuitive, and trustworthy partners for humans. By centering our research on the human side of interaction, we uncover the cognitive, social, and neural processes that shape how people perceive and collaborate with machines. Using both explicit behavioral measures and implicit neurocognitive signals, we develop evidence-based design principles that enhance human well-being, performance, and social connection. Using this approach, the BRAINS lab is currently investigating topics such as mind perception, human-machine teaming, joint-attention, joint-action, feedback processing, economic games, and aging. By investigating these topics, BRAINS Lab strives to prepare the next generation of scientists to build technologies that amplify human potential and improve everyday life.

Research team Publications Contact us

Research Team

Interested in joining? Click to email Dr. Abubshait!

Abdulaziz Abubshait, Ph.D.

Lab Director; Assistant Professor of Psychology

My research investigates how humans and machines interact, with the goal of designing machines, robots, and AI systems that serve as better partners in collaboration. By focusing on the human side of human–machine interaction, I identify the features that most effectively support and enhance human performance.

My work takes a comprehensive approach, combining explicit measures (such as self-report data and subjective ratings) with implicit measures (such as behavioral and physiological measures) to provide a deeper understanding of how people perceive, respond to, and work with machines. This integrated perspective allows us to translate fundamental insights into practical design principles that improve the way humans and machines engage with one another.

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Publications

Selected Works

Cavicchi, S., Abubshait, A., Mustile, M., Siri, G., & Ciardo, F. (2025). Can humanoid robots be used as a cognitive offloading tool? Cognitive Research: Principles and Implications.

Abubshait, A., Perez‐Osorio, J., De Tommaso, D., & Wykowska, A. (2024). Temporal interplay between cognitive conflict and attentional markers in social collaboration. Psychophysiology, 61(8), e14587.

Abubshait, A., Momen, A., Weis, P., & Wiese, E. (2023). Perceptual discrimination in the face perception of robots is attenuated compared to humans. Scientific Reports, 1(16708)

Marchesi, S., Abubshait, A., Kompatsiari, K., Wu, Y., & Wykowska, A. (2023). Cultural differences between Italians and Singaporeans in attention orienting when interacting with a mutually gazing robot. Scientific Reports. 13(11689).

Abubshait, A., Kompatsiari, K., Vescovo, V., Cardellicchio, De Tomasso, D., P., Fadiga, L., D’Ausilio, A., & Wykowska, A. (2023). Modulatory effects of communicative gaze on attentional orienting are driven by dmPFC but not rTPJ. Journal of Cognitive Neuroscience.

Abubshait, A., Parenti, L., Pérez-Osorio, J., & Wykowska, A. (2022). Misleading robot signals in a classification task induce cognitive workload as measured by theta synchronization between frontal and temporo-parietal brain regions. Frontiers in Neuroergonomics. 3(838136).

Abubshait, A., Siri, G. & Wykowska, A. (2022). Does attributing mental states to a robot influence accessibility during reading? Acta Psychologica, 228(103660).

Willemse, C., Abubshait, A., & Wykowska, A. (2022). Motor behaviour mimics the gaze response in establishing joint attention, but is moderated by individual differences in adopting the intentional stance towards a robot avatar. Visual Cognition, 30(1-2), 42-53.

Perez-Osorio, J.,* Abubshait, A.,* & Wykowska, A. (2021). Irrelevant Robot Signals in a Categorization Task Induce Cognitive Conflict in Performance, Eye Trajectories, the N2 Component of the EEG Signal, and Frontal Theta Oscillations. Journal of Cognitive Neuroscience, 34(1), 108-126.

Abubshait, A., McDonald, C. G., & Wiese, E. (2021). Examining social cognition with embodied robots: Does prior experience with a robot impact feedback-associated learning in a gambling task? Journal of Cognition, 4(1).

Abubshait, A., Beatty, P. J., McDonald, C. G., Hassall, C. D., Krigolson, O. E., & Wiese, E. (2021). A win-win situation: Does familiarity with a social robot influence feedback monitoring and learning? Cognitive, Affective, and Behavioral Neuroscience, 21, 763-775.

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Lab location

We're located in the fourth floor of Jabara Hall.