Karen Azmy, a recent June 2026 graduate of our BA/MA program in Psychology (Research Track) with a minor in Economics, was recently awarded the prestigious Best Poster Presentation Award at the International Association of Empirical Aesthetics (IAEA) conference.
Azmy’s award-winning poster presented findings from her thesis project, which tackles a fascinating frontier: using machine learning to understand human aesthetic perception.
To do this, Azmy looked at how we evaluate conservation photography. Specifically, she wanted to see if “uniqueness” metrics calculated by an artificial intelligence could predict how a human would rate an image’s uniqueness and aesthetic appeal.
Using a pretrained computer vision model called VGG16, she extracted image representations from multiple layers of the deep convolutional neural network, computed “latent distinctiveness” to mathematically quantify how visually unique each photo was in the model’s brain (its representational space), and compared the computer’s math with human ratings to see if AI processing aligns with human aesthetic preference.
“More broadly, the goal of my research is to bridge machine learning and cognitive neuroscience by using artificial neural networks as computational models to better understand the mechanisms underlying human visual perception and aesthetic experience.”
This achievement was made possible through months of hard work, support from the Office of Student Success, and the dedicated mentorship of her advisor, Dr. Vessel, along with her colleagues in the Visual NeuroAesthetics (VisNA) Lab.
Azmy will be presenting her research next at the Computational Cognitive Neuroscience (CCN) Conference, taking place right here in New York at NYU from August 3-6, 2026
