Vicente Estrada Gonzalez

Behavioral and Vision Scientist

As a behavioral and vision scientist, my research lives where eyes meet action. I use AI as a lens to uncover the principles behind human perception and behavior.

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Vicente Estrada

About Me

Theory of Mind Research at the University of Sydney

I work as a Senior Research Officer in the School of Psychology at the University of Sydney, where I study Theory of Mind—how people infer the thoughts, beliefs, and intentions of others.

Foveal attention in art viewing

During my PhD at UNSW Sydney, I used eye tracking to investigate how the visual system actively seeks relevant information. I analyzed the flow of visual data reaching the fovea—the center of our gaze—to explore how central vision guides our experience of art and natural scenes.
View my doctoral thesis

PTSD study

During my postdoctoral fellowship at the University of Pennsylvania, I expanded my focus beyond the lab to explore how people engage with art in rich, real-world contexts—museums, neighborhoods, and therapeutic settings.
One project focused on art therapy for individuals with PTSD, examining how trauma rehabilitation can be traced by looking at the aesthetics of their creations.
Read the article on Scientific Reports

Public art

Another project looked at how public art transforms the urban experience. We investigated how murals in Philadelphia shape sense of belonging, perceived safety, and emotional connection to their neighborhoods.
Read the preprint on SSRN

I also studied how slowing down the act of looking—through guided “slow looking” protocols—changes the depth and nature of aesthetic responses. Finally, I explored how digital encounters with artworks (e.g., on screens) compare with in-person museum experiences, particularly in how they affect emotional and cognitive engagement.

AI Research

I collaborate with the Penn Virtual Reality and Artificial Intelligence Lab, where we use AI-based tools to study human behavior. For example, we explore how models trained on visual behaviour and think-aloud analysis can predict complex mental states from basic emotions. This work builds on frameworks like the Penn taxonomy of aesthetic impacts, which provides a structured way to distinguish emotional, epistemic, and motivational dimensions of aesthetic experience.

The videos below show our pilot study. You can see how the model predicts basic emotions and complex cognitive states by analyzing what people say while looking at visual scenes and how their gaze behaves in real time.

Selected Publications

Google Scholar