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An Introduction to Differential Privacy

Anand D. Sarwate is an Associate Professor in the Department of Electrical and Computer Engineering at Rutgers, the State University of New Jerse, where he has been since 2014. He received a B.S. degree in Electrical Science and Engineering and a B.S. degree in Mathematics from MIT in 2002, an M.S. in Electrical Engineering from UC Berkeley in 2005 and a PhD in Electrical Engineering from UC Berkeley in 2008. From 2008-2011 he was a postdoctoral researcher at the Information Theory and Applications Center at UC San Diego and from 20112013 he was a Research Assistant Professor at the Toyota Technological Institute at Chicago, a philanthropically endowed academic computer science institute located on the University of Chicago campus. He was the Online Editor of the IEEE Information Theory Society (2015-2018) and an Associate Editor for the IEEE Transactions on Signal and Information Processing over Networks (2015-2018). Prof. Sarwate received the Rutgers Board of Trustees Research Fellowship for Scholarly Excellence in 2020, the the A. Walter Tyson Assistant Professor Award from the Rutgers School of Engineering in 2018, and an NSF CAREER award in 2015. His interests are in information theory, machine learning, and signal processing, with applications to distributed systems, privacy and security, and biomedical research. He is the author of several papers on differential privacy and differentially private machine learning, and has worked on applying differential privacy in biomedical applications. He has also given tutorial lectures on differential privacy at the Workshop on Information Forensics and Security (WIFS 2014) and the Neural Information Processing Systems (NeurIPS 2017) conference.