Rachel Greenstadt holds a bachelor’s degree in Computer Science (2001) and master’s degrees in Electrical Engineering and Computer Science (2002) from MIT, as well as a Ph.D. (2007) in Computer Science from Harvard. Her honors have included membership in the DARPA Computer Science Study Group, a U.S. Department of Homeland Security Fellowship, a PET Award for Outstanding Research in Privacy Enhancing Technologies, and a National Science Foundation CAREER Award.
Greenstadt's research has focused on designing more trustworthy intelligent systems — systems that act not only autonomously, but also with integrity, so that they can be trusted with important data and decisions. She takes a highly interdisciplinary approach to this research, incorporating ideas from artificial intelligence, psychology, economics, data privacy, and system security.
Prior to joining NYU, Greenstadt was an Associate Professor of Computer Science at Drexel University, where she ran the highly regarded Privacy, Security, and Automation Laboratory (PSAL) and served as an advisor to the Drexel Women in Computing Society. Before that, she was a Postdoctoral Fellow at Harvard’s School of Engineering and Applied Sciences, a Visiting Scholar with the University of Southern California TEAMCORE group, and a Research Intern at Lawrence Livermore National Laboratory. Throughout her career, she has edited multiple volumes of the journal Proceedings on Privacy Enhancing Technologies (PoPETs) and has been in demand as a peer reviewer. Greenstadt has chaired the ACM Workshop on Artificial Intelligence and Security multiple times and has regularly participated in, spoken at, and served on program committees for several other workshops building ties between the security, AI, and usability communities. She has long been an active speaker and participant in the international hacking community, and her work has been presented at Hacking at Random, Vierhouten, NL, ShmooCon, DefCon, and the Chaos Communication Congress.
Research Interests: Computer Science, Artificial Intelligence, Computer Security, Privacy