Signal Processing - July 2016 - 60

signal processing, computer vision, and machine learning,
with applications to radar imaging and biometrics. He is a
recipient of the 2016 Office of Naval Research Young
Investigator Award and the 2010 Oak Ridge Associated
Universities postdoctoral fellowship. He is member of Eta
Kappa Nu, Pi Mu Epsilon, and Phi Beta Kappa. He is a
Senior Member of the IEEE.
Rama Chellappa (rama@umd.edu) is a professor of electrical and computer engineering (ECE) and an affiliate professor of computer science at the University of Maryland,
College Park. He is also affiliated with the Center for
Automation Research, Institute for Advanced Computer
Studies (permanent member), and is the chair of the ECE
Department. In 2005, he was named a Minta Martin Professor
of Engineering. His current research interests are clustering;
three-dimensional modeling from video; image- and videobased recognition of objects, events, and activities; dictionarybased inference; compressive sensing; domain adaptation; and
hyperspectral processing. He is a Fellow of the IEEE, the
Association for Computing Machines, the International
Association of Pattern Recognition, the Optical Society of
America, the American Association for the Advancement
of Science, and the Association for the Advancement of
Artificial Intelligence.
Deepak Chandra (dchandra@google.com) heads
authentication in the Machine Intelligence and Research
group at Google Inc., Mountain View, California. The project aims to completely redefine authentication for the digital
and physical worlds. Prior to this, he was the program lead
in Google's Advanced Technology and Projects organization, where he headed all product engineering and design for
mobile authentication projects. He defined company-wide
authentication strategy for Motorola prior to leading the
efforts at Google. He has developed multiple wearable
authentication products, including Motorola Skip and
Digital Tattoo.
Brandon Barbello (bbarbello@google.com) is a product
manager at Google Research and Machine Intelligence, where
he works on privacy-sensitive, on-device machine learning.
He was previously involved with the Google Advanced
Technology and Projects organization on the Project Abacus
team, where he managed efforts to develop a multimodal continuous authentication system for smartphones. Prior to his
time at Google, he cofounded four companies in electronics,
fintech, and private equity.

References

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[1] N. Clarke and S. Furnell, "Authentication of users on mobile telephones: A survey of attitudes and practices," Comput. and Security, vol. 24, no. 7, pp. 519-527,
2005.

[26] M. E. Fathy, V. M. Patel, and R. Chellappa, "Face-based active authentication
on mobile devices," in Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing, 2015, pp. 1687-1691.

[2] A. Vance. (2010, Jan. 20). If your password is 123456, just make it hackme
[Online]. Available: http://www.nytimes.com

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face detection for continuous authentication," in Proc. IEEE Int. Conf. Image Processing, 2016.

[3] A. J. Aviv, K. Gibson, E. Mossop, M. Blaze, and J. M. Smith, "Smudge attacks
on smartphone touch screens," in Proc. 4th USENIX Conf. Offensive Technol., 2010,
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Industry solution falls short, while legislative efforts to curb theft continue [Online].
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60

[28] P. Abeni, M. Baltatu, and R. D'Alessandro, "Nis03-4: Implementing biometrics-based authentication for mobile devices," in Proc. IEEE Global Telecommun.
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IEEE Signal Processing Magazine

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July 2016

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http://www.nytimes.com http://www.consumerreports.org/cro/news/2014/04/smart-phone-thefts

Table of Contents for the Digital Edition of Signal Processing - July 2016

Signal Processing - July 2016 - Cover1
Signal Processing - July 2016 - Cover2
Signal Processing - July 2016 - 1
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Signal Processing - July 2016 - Cover3
Signal Processing - July 2016 - Cover4
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