Biography:Farinaz Koushanfar

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Short description: Computer scientist
Farinaz Koushanfar
Farinaz Koushanfar.jpg
Education
AwardsIEEE Fellow
Scientific career
Institutions
ThesisEnsuring data integrity in sensor-based networked systems (2005)
Doctoral advisor
  • Alberto Sangiovanni-Vincentelli
  • Miodrag Potkonjak
Websitefarinaz.eng.ucsd.edu

Farinaz Koushanfar is an Iranian-American computer scientist[1] whose research concerns embedded systems, ad-hoc networks, and computer security. She is a professor and Henry Booker Faculty Scholar of Electrical and Computer Engineering at the University of California, San Diego.[2]

Education and career

Koushanfar obtained her bachelor's degree in electrical engineering from Sharif University of Technology (BSEE 1998), a master's degree in electrical engineering and computer science from the University of California, Los Angeles in 2000, and a second master's degree in statistics and Ph.D. in electrical engineering and computer science from the University of California, Berkeley in 2005,[2] with the dissertation Ensuring data integrity in sensor-based networked systems jointly supervised by Alberto Sangiovanni-Vincentelli and Miodrag Potkonjak.[3][4]

After postdoctoral research at the University of Illinois Urbana-Champaign, she joined the faculty of Rice University in 2006. She moved to her present position in San Diego in 2015.[2]

Recognition

In 2008, Koushanfar was listed in the MIT Technology Review "35 Innovators Under 35" for her work using random variation in integrated circuits as a device fingerprint allowing manufacturers to validate the authenticity of devices.[5] Her 2008 paper "Lightweight Secure PUFs" was given the Ten Year Retrospective Most Influential Paper Award in 2017 at the International Conference on Computer Aided Design.[6]

She was named a Presidential Early Career Award for Scientists and Engineers in 2010[7] and an IEEE Fellow in 2019, "for contributions to hardware and embedded systems security and to privacy-preserving computing".[8] She was named to the 2022 class of ACM Fellows, "for contributions to secure computing and privacy-preserving machine learning".[9]

Selected publications

Resources

External links