Associate Professor, Electrical and Computer Engineering
Courtesy Appointment, Computer Science
Carnegie Mellon University
Building 23 (MS 23-11)
Moffett Field, CA 94035
Anupam Datta is an Associate Professor (with tenure) at Carnegie Mellon University where he holds a primary appointment in the Electrical and Computer Engineering Department and a courtesy appointment in the Computer Science Department. His research area is security and privacy, with an emphasis on bridging theory and practice. Datta's current focus is on information accountability: foundations and tools that can be used to provide oversight of complex information processing ecosystems (including big data systems) to examine whether they respect privacy, and other desirable values in the personal data protection area, such as fairness and transparency.
His research group produced the first complete logical specification and audit of all disclosure-related clauses of the HIPAA Privacy Rule for healthcare privacy. His group's work with Microsoft Research produced the first automated privacy compliance analysis of the production code of an Internet-scale system -- the big data analytics pipeline for Bing, Microsoft's search engine.
Datta has also made significant contributions to the research area of compositional security. Specifically, his work led to new principles for securely composing cryptographic protocols and their application to several protocol standards, most notably to the IEEE 802.11i standard for wireless authentication and to attestation protocols for trusted computing. Datta has authored a book and over 50 other publications on these topics. He serves as an Editor-in-Chief of Foundations and Trends in Privacy and Security, an Associate Editor of the Journal of Computer Security and the Journal of Computer and System Sciences, as well as the 2013-14 Program Co-Chair of the IEEE Computer Security Foundations Symposium. Datta obtained Ph.D. (2005) and M.S. (2002) degrees from Stanford University and a B.Tech. (2000) from IIT Kharagpur, all in Computer Science.
- Algorithmic Transparency via Quantitative Input Influence [The Conversation] [FAT/ML'16 Invited Talk]
- Algorithmic Accountability via Information Flow Experiments [Application: FAQ on Discrimination in Online Behavioral Advertising]
- Bootstrapping Privacy Compliance in Big Data Systems [Application: Web privacy, in particular, deployed compliance tool for Bing]
EducationB. Tech., Computer Science, IIT Kharagpur, 2000
M.S., Computer Science, Stanford University, 2002
Ph.D., Computer Science, Stanford University, 2005
- 2017: DARPA Safe Machine Learning, Data Privacy@Simons Institute, Data Economy@Telecom ParisTech, PLSC@Berkeley, Algorithms and Explanations@NYU
- 2016: FAT/ML@NYU, BigData@CSAIL Data Privacy Series at MIT, Safe AI@CMU + White House OSTP, Formal Methods and Security@PLDI'16, Security and Human Behavior'16@Harvard, Privacy Engineering@Oakland'16, John Mitchell Festscrift@Stanford, Science of Security@CPSWeek'16, FTC PrivacyCon'16
Accountable Decision Systems [Lead PI; NSF large collaborative involving CMU, Cornell, ICSI]
Conference on Fairness, Accountability, and Transparency [Steering Committee]
Foundations and Trends in Privacy and Security [Editor-in-Chief]
IEEE Computer Security Foundations Symposium [Steering Committee]