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P. Jonathon Phillips (Fed)

Dr. P. Jonathon Phillips is an Electronic Engineer at the National Institute of Standards and Technology's Information Technology Laboratory. Jonathon is a leading researcher in the fields of computer vision, face recognition, biometrics, and forensics.    He has published over 100 peer reviewed papers in face recognition, computer vision, biometrics, psychology, forensics, statistics, and neuroscience. His papers have received over 38,000 Google citations.  He is an IEEE Fellow and an International Association of Pattern Recognition (IAPR) Fellow.

Dr. Phillips pioneered competitions to improve technology in face recognition, computer vision, and biometrics. The programs and competitions that Jonathon managed were instrumental in advancing face recognition from its infancy in research labs to deployment in real-world applications. Progress was measured in a series of evaluations from the 1993 FERET competition through the Multiple Biometric Evaluation 2010. The competitions documented a Moore’s law improvement in face recognition accuracy—from 1993 to 2010, the error rate for the technology decreased by half every two-years. For his work on competitions and its influences and adoption by computer vision and biometrics he won the IEEE inaugural Mark Everingham Prize, the NIST Distinguished Career Award, the IEEE Biometrics Council Leadership Award, FedID Career Achievement Award, two Dept. of Commerce Gold Medal (2003 and 2020), the Dept. of Commerce Bronze Medal, Office of the Secretary of Defense Medal for Exceptional Civilian Service, and Federal Bureau of Investigation CJIS Assistant Director’s Award for Outstanding Scientific Achievement. 

A hallmark of Jonathon’s research is collaboration with researchers from related fields. These collaborations have resulted in better understanding of biometric algorithm performance and the relationship between human and algorithm face recognition accuracy. 

In law enforcement, border control, and security, humans perform face recognition. To assess the ability of technology to complement or perform face recognition task, it is necessary to know the relative accuracy of machines and humans.  Working with collaborators, Jonathon pioneered the development of methods to compare human and machine performance and systematically incorporated measuring human performance into face recognition competitions. This line of research showed that face recognition algorithms accuracy can vary by race and led to calls to test face recognition systems for racial bias. In the wake of the National Academies report on Forensics Sciences, this work was adapted to measuring the accuracy of facial forensic examiners and people with superior face recognition ability—facial super-recognizers.  This research confirmed that facial forensic examiners and super-recognizers have superior face recognition ability.

To understand how lighting, camera, pose, environment and other factors affect face recognition performance, Jonathon and his collaborators developed statistical methods to analysis face recognition and biometric performance. To assess the state-of-the-art across multiple studies they applied and adapted meta-analysis for biometrics.  Both these accomplishments laid foundation for understanding where and how to apply biometric systems. This work resulted in a best paper and two best reviewed paper awards.  

In addition to working for NIST since 1997, Dr. Phillips was assigned to the Defense Advanced Projects Agency (DARPA) as a program manager, from 2000-2004. From 2002-2012, he served on the Executive Office of the President (White House) National Science and Technology Council Subcommittee on Biometrics.  His work has been reported in print media of record including the New York Times and the Economist. He has appeared on NPR’s ScienceFriday. Discover magazine stated, “P. Jonathon Phillips is considered the most influential scientist in facial recognition.”  He was an Associate Editor for the IEEE Trans. on Pattern Analysis and Machine Intelligence and guest editor of a special issue of the Proceedings of the IEEE on biometrics. 


NIST Distinguished Career Award, 2022

FedID Service and Leadership Award (to IAD Image Group), 2022

FedID Career Achievement Award, 2021

US Department of Commerce Gold Medal, 2020

IEEE Biometrics Council Leadership Award, 2018

Best Reviewed Paper, International Joint Conference on Biometrics, 2014

Inaugural IEEE Computer Society Mark Everingham Prize, 2013

Best Paper Award, IEEE Conference BTAS, 2013

Best Poster Award, IEEE Conference BTAS, 2013

Federal Bureau of Investigation CJIS Assistant Director’s Award for Outstanding Scientific Achievement, 2011

IEEE Conference BTAS Distinguished Speaker Award, 2010

IEEE Fellow, 2010

US Department of Commerce Bronze Medal, 2008

International Association of Pattern Recognition (IAPR) Fellow, 2008

Best Paper Award, IEEE Conference on Face & Gesture, 2008

Best Reviewed Paper, IEEE Conference BTAS, 2007

Office of the Secretary of Defense Medal for Exceptional Civilian Service, 2004

US Department of Commerce Gold Medal, 2003

NEC Gorenstein Fellowship, 1992


NIST Explainable AI Workshop Summary

P. Jonathon Phillips, Carina Hahn, Peter Fontana, Amy Yates, Matthew Smith
This report represents a summary of the National Institute of Standards and Technology (NIST) Explainable Artificial Intelligence (AI) Workshop, which NIST held
Created October 9, 2019, Updated December 8, 2022