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Elaine Shi is an assistant professor of computer science and a member of the Maryland Cybersecurity Center.
Her research generally focuses on security, privacy, and applied cryptography. In her work, she takes a unique approach where she combines theoretic innovations with practical system design and implementation. Shi’s research spans a wide range of topics, including computation on encrypted data, privacy-preserving data mining, system security, sensor network and vehicular network security, usable authentication, secure storage systems, and more.
She has published more than 50 scholarly publications, and her work has received more than 4,000 citations. Aside from security and privacy, Shi is also interested in data mining. In particular, she and her team won the IJCNN/Kaggle Social Network Challenge in 2011.
Shi is the recipient of a Sloan Research Fellowship, a Google Research award (2013, 2014), an NSA Best Scientific Cybersecurity Paper award, a UMD Invention of the Year award, and an ACM CCS Best Student Paper award.
She received her doctorate and master’s in computer science from Carnegie Mellon University, and her B.E. from Tsinghua University. Before coming to the University of Maryland, she was also a member of research staff at Palo Alto Research Center (PARC) and a research scientist at University of California, Berkeley.
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