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

Face Perception Research Lab


Principal Investigator

Alice O'Toole

Alice O’Toole, PhD

Prof. Alice O’Toole is a Professor in the School of Behavioral and Brain Sciences at The University of Texas at Dallas and currently holds the Aage and Margareta Møller Endowed Chair.

Her research interests include human perception, memory, and cognition, with an emphasis on computational approaches to modeling human information processing. Most recently, her work is focused on the problem of recognizing faces and people. She has approached this problem using methods from psychology, cognitive neuroscience, and computational modeling. Current projects in her lab include comparisons between human and machine-based face recognition, the analysis of face recognition algorithms, person recognition from face, body, and biological motion, and modeling the relation between language and human body shapes. Read more

View Dr. O’Toole’s Curriculum Vitae


Eilidh Noyes

Eilidh Noyes

Eilidh obtained a MA psychology degree from the University of Glasgow (2013), followed by a PhD in psychology at the University of York (2016). Eilidh’s research background includes human face recognition in challenging conditions (image manipulations, viewing distance, extremely similar faces and deliberate disguise), the role of familiarity in face perception and methods for improving face recognition performance. Her current projects include the investigation of forensic experts’ face recognition capabilities, context dependent face learning, machine face recognition, and person perception.


Noyes, E & Jenkins, R. (2017) Camera-to-subject distance affects face configuration and perceived identity. Cognition. 165, 97-104.

Sanders, J. G., Ueda, Y., Minemoto, K., Noyes, E., Yoshikawa, S., & Jenkins, R. (2017). Hyper-realistic masks: a new challenge in person identification. Cognitive Research: Principles and Implications. 2:43

Noyes, E., Phillips, P. J., & O’Toole, A. J. (2017). What is a Super-Recogniser? In M. Bindemann & A. M. Megreya (eds.) Face processing: Systems, Disorders, and Cultural Differences. 173-201. New York, NY: Nova.

Noyes, E., & O’Toole, A. J. (2017). Face recognition assessments used in the study of super-recognisers. arXiv, arXiv1705.04739.

Noyes, E. & Jenkins, R. (2017). Improving Performance on a Difficult Face Matching Task. Perception, 46, 226.

Robertson, D. J., Noyes, E., Dowsett, A., Jenkins, R., & Burton, A. M. (2016). Face recognition by Metropolitan Police Super-recognisers. Plos One, 11, e0150036.

Noyes, E., & Jenkins, R. (2016). Deliberate disguise in facial image comparison. Journal of Vision, 16(12), 924.

Publication List on Google Scholar

Graduate Students

Carina A. Hahn

Carina A. Hahn, MS (Doctoral Student)

Carina is working toward a PhD, with a focus on high level vision. She earned a BS in Psychology from Texas A&M University in 2011. Currently, her primary interests are in the psychological and neural processing of unfamiliar and familiar faces and bodies. We encounter familiar and unfamiliar people in motion and in a variety of contexts and viewing conditions, and yet we are able to recognize people we know despite this large variability. Information from the face and body allow people to perform this task with high accuracy. With behavioral studies, Carina has examined how the quality of the information from the face and body in natural viewing conditions contributes to recognition. Using functional neuroimaging and pattern-based classification techniques, she examines the neural correlates of recognition when we view people as we see them in the real world. For her most up-to-date information and CV, visit


Hahn, C. A., & O’Toole, A. J. (2017). Recognizing approaching walkers: Neural decoding of person familiarity in cortical areas responsive to face, bodies, and biological motion. NeuroImage. 146, 859-868. doi: 10.1016/j.neuroimage.2016.10.042.

Hill, M. Q., Streuber, S., Hahn, C. A., Black, M. J., & O’Toole, A. J. (2016). Creating body shapes from verbal descriptions by linking similarity spaces. Psychological Science. 27(11), 1486-1497. doi: 10.1177/0956797616663878.

Streuber, S., Quiros-Ramirez, M. A., Hill, M. Q., Hahn, C. A., Zuffi, S., O’Toole, A., & Black, M. J. (2016). Body Talk : Crowdshaping Realistic 3D Avatars with Words. ACM Trans. Graph. (Proc. SIGGRAPH). 35(4), 54:1-54:14.

Hahn, C. A., O’Toole, A.J., Phillips, P. J. (2016). Dissecting the time course of person recognition in natural viewing environments. British Journal of Psychology. 107(1), 117-134. doi: 10.1111/bjop.12125

White, D., Phillips, P.J, Hahn, C.A., Hill, M., & O’Toole, A.J. (2015). Perceptual expertise in forensic facial image comparison. Proceedings of the Royal Society of London B: Biological Sciences, 282, 1814-1822. doi: 10.1098/rspb.2015.1292

Matthew Hill

Matthew Q. Hill, BS (Doctoral Student)

Matt is a PhD student interested in the relationship between human cognition and machine learning. He has recently investigated the relationship between human body shapes and the language used to describe them by systematically linking 3D body scans with verbal body descriptions. He now works as part of a team evaluating computer face recognition systems in order to improve their performance.


Hill, M. Q., Streuber, S., Hahn, C. A., Black, M. J., & O’Toole, A. J. (2016). Creating Body Shapes From Verbal Descriptions by Linking Similarity Spaces. Psychological Science, 27(11), 1486-1497.

Streuber, S., Quiros-Ramirez, M. A., Hill, M. Q., Hahn, C. A., Zuffi, S., O’Toole, A., & Black, M. J. (2016). Body talk: Crowdshaping realistic 3D avatars with words. ACM Transactions on Graphics (TOG), 35(4), 54.

White, D., Phillips, P.J, Hahn, C.A., Hill, M. Q., & O’Toole, A.J. (2015). Perceptual expertise in forensic facial image comparison. Proceedings of the Royal Society of London B: Biological Sciences, 282, 1814-1822. doi: 10.1098/rspb.2015.1292

Phillips, P. J., Hill, M. Q., Swindle, J. A., & O’Toole, A. J. (2015). Human and algorithm performance on the PaSC face Recognition Challenge. In Biometrics Theory, Applications and Systems (BTAS), 2015 IEEE 7th International Conference on (pp. 1-8). IEEE.

Asal Baragchizadeh

Asal Baragchizadeh, MS, MPA (Doctoral Student)

Asal is a third-year PhD student in the Cognition and Neuroscience program. She received a MS in Applied Cognition and Neuroscience from the University of Texas at Dallas, MPA from Northeastern University, and a double-major BS in Biomedical and Electrical Engineering from Tehran Science and Research University in Iran. Currently, her primary interest is in person identification from biological motion and its neural correlates. More specifically, using fMRI-adaptation she is studying the discriminability of neural activity patterns elicited in response to identity and actions in selected ROIs and whole brain. Previously, she worked on a project to evaluate Automated Identity Masking (AIM) algorithms in Naturalistic Driving Study (NDS) videos. As a side research project, she has helped a team of researchers at the US Army Graduate Program in Anesthesia Nursing, JBSA-FSH, San Antonio TX to study the effects of tibial and humerus intraosseous administration of epinephrine in a cardiac arrest swine model.


Asal Baragchizadeh, Thomas Karnowski, David Blome, & Alice O’Toole (2017). Evaluation of the Automated Identity Masking Method (AIM) in Naturalistic Driving Study (NDS). Twelfth IEEE International Conference on Automatic Face and Gesture Recognition.

Beaumont, D., Baragchizadeh, A., Johnson, C., & Johnson, D. (2017). Effects of tibial and humerus intraosseous administration of epinephrine in a cardiac arrest swine model. American Journal of Disaster Medicine, 11(4), 243-251.

Ying Hu

Ying “Nina” Hu (Doctoral Student)

Ying is a PhD student who is interested in visual perception and cognition. She is currently working on exploring the social inference from body shapes. She also works in the team designing a test to measure the skills of forensic face identification examiners on challenging tasks.


Hu, Y., Jackson, K., Yates, A., White, D., Phillips, P. J., & O’Toole, A. J. (2017). Person recognition: Qualitative differences in how forensic face examiners and untrained people rely on the face versus the body for identification. Visual Cognition, 1-15.

Géraldine Jeckeln

Géraldine Jeckeln

Géraldine is a second year Master’s student in the Applied Cognition and Neuroscience program. She graduated from Concordia University with a bachelor’s degree in Honours Psychology where she focused her research on visual eccentricity-dependent effects involving illusory face distortions. Her current research investigates wisdom-of-crowds effects in face recognition and she is involved in a project investigating the performance of forensic face identification examiners.

Connor Parde

Connor Parde, BS (Doctoral Student)

Connor is a PhD student in the Cognition and Neuroscience program. He is interested in face recognition, decision making, and computational modeling of human cognition. His current research focuses on analyzing the performance of facial recognition algorithms across difficult imaging conditions, with emphasis on the nature of the face representation stored by the network.

Jacqueline G. Cavazos

Jacqueline G. Cavazos

Jackie is a first-year PhD student in the Psychological Sciences program. She received a BA in Psychology from California State University, Fullerton where she focused on examining the effects of disguise and race on face recognition. Jackie is interested in how face recognition performance is effected in challenging situations and how it can be improved. She has recently explored how image presentation type (contiguous and distributed learning) influences own- and other-race face recognition performance. Currently, Jackie is assisting in designing a follow-up study to examine the other-race effect in professional forensic facial examiners.

Lab Affiliated Graduate Student

James Ryland

James Ryland (Doctoral Student)

James is a PhD student studying with Dr. Richard Golden and Dr. O’Toole, who carries out research on visual cognition and neuroscience. He designs and implements neural network models for object recognition that are consistent with cognitive theories of how the brain performs visual recognition. In addition, he tests these models to see if their behavior and representations are consistent with human behavior and neural organization. Although now focused on visual recognition, James has many other interests such as self-organization, spatial awareness, motor planning, and visualization.

Undergraduate Students

Yolanda Ivette Colon

Yolanda Ivette Colon

Ivette is a senior at The University of Texas at Dallas, studying Cognitive Science with a minor in Computer Science. Her current research is focused on analysis of the output from facial recognition algorithms. She is particularly interested in face recognition, computational modeling, neural networks, and algorithmic analysis. After graduating in Fall 2017, she intends to pursue graduate studies in computational modeling for cognition.

Kelsey Jackson

Kelsey Jackson

Kelsey is a sophomore at The University of Texas at Dallas, majoring Cognitive Science with a minor in Creative Writing. Areas of interest include facial recognition, perception, cognitive media theory, and vision science. She is currently working on a statistical item analysis for forensics facial examiners as an undergrad assistant. After graduation, she plans to pursue a graduate degree in vision science or cognitive neuroscience.

Rahel Usman

Rahel Usman

Rahel is a junior at The University of Texas at Dallas. She is a pre-med student working to get into medical school after completing her bachelor’s degree in Cognitive Science. She is working on a study of face recognition study as an undergrad research assistant.


Fang Jiang, PhD – Assistant Prof at U Nevada at Reno (See bio)

Vaidehi Natu, PhD – Post-doctoral Fellow at Stanford (See bio)

Allyson Rice

Dana Roark, PhD – Instructor in BBS at UT Dallas

Alumni with Dr. O'Toole

(Dr. O’Toole with lab alumni)