The University of Texas at Dallas School of Behavioral and Brain Sciences

Face Perception Research Lab

Our Research

The human face is a captivating and compelling visual stimulus that provides us an entry point into our interactions with others. From the face, we can perceive a unique identity, a gender, an ethnicity/race and an approximate age. We can remember hundreds, if not thousands, of individual faces. As the face changes, it provides us with moment-to-moment emotional and social signals in the form of facial expressions and gestures. These signals guide us through social interactions and help us to form memories.

In our research, we study human perception and memory for faces and people, using methods from experimental psychological, cognitive neuroscience and computational vision. The projects in our lab can be divided into categories. The first includes studies of human perception and memory for faces. The second involves comparisons between humans and state-of-the-art machine-based face recognition systems. In the third category, we are conducting studies examining the neural representations that make human face recognition possible, using functional magnetic imaging tools.

See all of our individual research projects.


Scroll below for more news!

Jackie Cavazos successfully defended her Dissertation Proposal: Does Race Matter? Testing Parameters for Collaboration Benefits of Face Identification Accuracy. Congratulations Jackie!

Jackie Cavazos was invited to give a talk at the Demographic Variation in the Performance of Biometric Systems Workshop for the Winter Conference on Applications of Computer Vision in Aspen, CO.

Victoria Huang received the Patti Henry Pinch Scholarship for Undergraduate Research and the Santrock Undergraduate Travel Award. Congrats Victoria!

Check out Alice O’Toole’s discussion on human vs machine facial recognition in The Promise and Perils of Facial Recognition, SciLine AAAS!

Ying (Nina) Hu published a paper titled Integrating faces and bodies: Psychological and neural perspectives on whole person perception in Neuroscience & Biobehavioral Reviews. Congratulations!

Connor Parde’s abstract, Integrating Single-Unit and Pattern Codes in DCNNs Trained for Face Identification, was accepted for a talk at the 20th annual Vision Sciences Society meeting. Congrats Connor!

Asal Baragchizadeh, Yolanda (Ivette) Colon, Ying (Nina) Hu, Gerie Jeckeln, and Jackie Cavazos each had their abstracts accepted for poster presentations at the 20th annual Vision Sciences Society meeting. Nicely done everyone!

Matt Hill published a paper in Nature Machine Intelligence titled Deep convolutional neural networks in face of caricature. Congrats!

Victoria Huang and Snipta Mallick join the Face Perception Research Lab. Welcome!

Congratulations to Connor Parde who received the 2019 Carol L. and Maynard S. Redeker Fellowship!

Ying (Nina) Hu received the 2019 Bio-Behavioral Sciences Research Award. Congratulations!

Connor Parde published a paper in Cognitive Science titled Social Trait Information in Deep Convolutional Neural Networks Trained for Face Identification. Congrats!

Face Perception Research Lab

(Top) Yolanda (Ivette) Colon; (Left to right) Asal Baragchizadeh, Victoria Huang, Gerie Jeckeln, Matt Hill, Connor Parde, Jackie Cavazos, Snipta Mallick, Ying (Nina) Hu; (Center) Alice O’Toole and Glen