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Priya Narasimhan

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Title: Priya Narasimhan  
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Subject: Fault tolerance, List of University of California, Santa Barbara alumni
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Priya Narasimhan

Priya Narasimhan
Occupation Professor, Carnegie Mellon University
Founder and CEO, YinzCam

Priya Narasimhan is a Professor of Electrical & Computer Engineering at Carnegie Mellon University in Pittsburgh, Pennsylvania.[1][2] She is also the founder of YinzCam, a mobile app development company that provides official apps for a number of professional sports teams.[3]

Narasimhan was born in India and lived in Africa.[4] She attended University of California, Santa Barbara.[4] Her academic interests include dependable distributed systems, fault-tolerance, embedded systems, mobile systems and sports technology.[4] She received a Sloan Fellowship.[1] She has served as co-director of Mobility Research Center at Carnegie Mellon University.[4] She has written extensively on fault tolerance, research that led to the development of the Fault Tolerant CORBA industrial standard.[1] Her Ph.D. research was commercialized through Eternal Systems, Inc., a company where she served as Chief Technology Officer and Vice-President of Engineering.[1] Her research led to the development of 24x7 highly available platforms and solutions for data centers and large online systems.[1]

She became a fan of the Pittsburgh Penguins upon moving to Pittsburgh in 2001.[3] She is also a fan of the Pittsburgh Steelers.[1]

Her interest in computers and Pittsburgh-based sports led her to develop mobile apps bringing real-time statistics, multimedia, streaming radio, social media, and live video feeds.[5] She has incorporated YinzCam into her Sports Technology course at Carnegie Mellon University.[6] Through Yinzcam, she also developed iBurgh, a groundbreaking mobile app to allow citizens to report complaints to the city's IT departments via smartphones.[4][7]

She had also developed AndyVision, a robot project funded by the Intel Science and Technology Center at Carnegie Mellon University that is capable of quickly inventorying merchandise and detecting out-of-stock conditions in retail environments.[8]


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