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NIST Information Technology Professionals Recognized for Excellence

From NIST Tech Beat: March 26, 2014

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Contact: Evelyn Brown
301-975-5661

Three employees of the National Institute of Standards and Technology (NIST) recently received awards for their national and international contributions to information technology.

Naomi LefkovitzMatthew SchollJonathon Phillips
Naomi Lefkovitz
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Matthew Scholl
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Jonathon Phillips
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On March 20, 2014, two NIST employees received the 2014 Federal 100 Award. Recipients are chosen from government, industry and academia. The Federal 100 are selected by government and industry leaders convened by Federal Computer Week.

Senior Privacy Policy Advisor Naomi Lefkovitz was chosen for her efforts to safeguard privacy in the identity-management initiative being developed via the National Strategy for Trusted Identities in Cyberspace.

Computer Security Division Deputy Chief Matthew Scholl was named for his role in leading the development of the recently released Cybersecurity Framework—called for by an executive order issued by President Obama, NIST's actions in response to the Digital Government Strategy and the government goals for improved cybersecurity.

Facial recognition researcher Jonathon Phillips received the inaugural Everingham Prize from the Institute of Electrical and Electronics Engineers (IEEE) Pattern Analysis and Machine Intelligence (PAMI) Technical Committee for his contributions to the computer vision community. The award is in memory of Mark Everingham, a leader in the facial recognition field. IEEE is the world's largest professional association for the advancement of technology.

Phillips is an electronic engineer who works in automatic, psychological and neuroscience aspects of face and person recognition. He was recognized for establishing evaluations and challenges as a standard methodology in the computer vision field.

His current goals are to develop challenge problems to advance the technology and science of face and person recognition, including recognition of video taken by handheld cell phones, adapting face recognition for social media networks, and developing face and person recognition algorithms that outperform humans.