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Reza Shokri is a NUS Presidential Young Professor of Computer Science. His research focuses on trustworthy machine learning, quantitative analysis of data privacy, and design of privacy-preserving algorithms for practical applications, ranging from data synthesis to collaborative machine learning. He is an active member of the security and privacy community, and has served as a PC member of IEEE S&P, ACM CCS, Usenix Security, NDSS, and PETS. He received the Caspar Bowden Award for Outstanding Research in Privacy Enhancing Technologies in 2018, for his work on analyzing the privacy risks of machine learning models, and was a runner-up in 2012, for his work on quantifying location privacy. He obtained his PhD from EPFL.
Data and Machine Learning Privacy
Trustworthy Machine Learning