My research goal is to develop science and technology to account for information flows in complex systems, in particular, systems in which security, privacy, and fairness are of central importance. My work has helped develop the research areas of Privacy through Accountability and Compositional Security. Methodologically, my work involves formalizing nuanced concepts (e.g., notions of privacy and transparency) and reasoning that complex programs (e.g., for big data analytics and cryptography) respect these formal properties. I am affiliated with the CMU Security and Privacy Institute and the Principles of Programming group.
- Algorithmic Transparency via Quantitative Input Influence [Application: Predictive policing] [FAT/ML'16 Invited Talk]
- Algorithmic Accountability via Information Flow Experiments [Application: FAQ on Discrmination in Online Behavioral Advertising]
- Bootstrapping Privacy Compliance in Big Data Systems [Application: Web privacy, in particular, deployed compliance tool for Bing]
- Privacy and Contextual Integrity [ The Economist ][White House Consumer Privacy Bill of Rights]
- Recent/Upcoming talks: Privacy and Accountability at (Invited) FAT/ML@NYU, (Invited) BigData@CSAIL Data Privacy Series at MIT, (Invited) Safe AI@CMU + White House OSTP, (Invited) Formal Methods and Security@PLDI'16, (Invited) Security and Human Behavior'16@Harvard, (Keynote) Privacy Engineering@Oakland'16, (Invited) John Mitchell Festscrift@Stanford, (Keynote) Science of Security@CPSWeek'16, FTC PrivacyCon'16