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SAN DIEGO, CALIFORNIA – January 23, 2023 – Farinaz Koushanfar, professor of electrical and computer engineering at the University of California, San Diego and Henry Booker Scholar, has been named one of 57 Fellows of the Association for Computing. was Machinery (ACM) for 2022. Koushanfar is recognized for his contributions to secure computing and privacy-preserving machine learning.
The ACM Fellows Program recognizes the top 1% of ACM members for outstanding achievement in computing and information technology and outstanding service to ACM and the greater computing community.
Director Khoshanfar Adaptive computing and embedded systems (ACES) Laboratory at the University of California, San Diego. Her lab work has transformed the important areas of hardware-based security, secure AI, and privacy-preserving computing. Koushanfar is Machine Intelligence, Computing and Security Center (MICS)is an engineering research center at the UC San Diego Jacobs School of Engineering focused on innovation and diverse workforce development through the integration of hardware, software, AI algorithms, and data for scalable machine learning and security.
“I am honored to be recognized by this respected class of ACM Fellows,” said Khoshanfer. “I am most excited about the long-term prospects and potential societal impact of my work in security, privacy and AI. I am grateful for the privilege given to me by the community and would like to extend my heartfelt gratitude to I would like to thank my mentors, collaborators, postdocs and students for their unwavering support and contributions to our joint project. ”
Koushuanfur’s initial contributions to the field of computing were far-reaching. Her research has resulted in widely used software and dozens of patents filed in the United States and around the world. Her notable inventions ensure the security of digital integrated circuits (ICs) and their software/data, the robustness of AI models, and privacy-preserving computation.
She invented the first-ever methodology to actively and independently lock, track, and control each IC post-manufacture. Koushanfar’s two recent patent-pending works define state-of-the-art techniques for the difficult problem of cryptographically secure deep learning on encrypted data.
Koushanfar is also the inventor of the first hardware accelerator for safe deep learning that is robust against adversarial samples and the first AI accelerator that is robust against data poisoning. She is the inventor of the first deep learning watermarking method that is simultaneously robust against several classes of known vulnerabilities. Koushanfar is also a prominent advocate for women and minorities and has led several of her DEI initiatives. Under her leadership she (and she worked with the MICS Co-Director), both the UCSD ACES Lab and her MICS Center are now the most gender-balanced in the world, both in terms of students and faculty. She is one of the engineering research groups who took it.
ACM President Yannis Ioannidis said in a statement: “But individual contributions are essential links in the chain. As we elect our new class of ACM Fellows, we hope that learning about these leaders will give us insight into their own work and inspire our wider membership.”
Prior to ACM accreditation, Koushanfar’s influential publications have won several best paper awards at leading conferences in her field. She was named one of the top 35 innovators in the world under the age of 35 by the 2008 MIT Technology Review (TR-35) and received the Presidential Early Career Award for Scientists and Engineers from President Obama in 2010. In 2019, he received the rank of Fellow of the U.S. Institute of Electrical and Computer Engineers, and the Most Influential Paper Award of the Decade Retrospective at the 2017 International Conference on Computer Aided Design.
Koushanfar is currently participating in a diverse class of 2022 ACM Fellows representing research centers, universities and private companies based in 10 countries around the world. Fellows are nominated by their peers and nominations are reviewed by a distinguished selection committee.
