Aaron Bembenek

computer scientist ❊ reader of books ❊ fisher of fish

Aaron Bembenek

I am a computer science PhD candidate at the Harvard John A. Paulson School of Engineering and Applied Sciences, where I am a member of the programming languages group. I am advised by Stephen Chong. My primary research interests are static analysis, logic programming, and security. I have also contributed to multidisciplinary work bridging legal and technical definitions of privacy (with Kobbi Nissim and Alexandra Wood).

My undergraduate degree is in classics from Princeton University. I enjoy reading and spending time outdoors.

Going Into Greater Depth in the Quest for Hidden Frames
João Gonçalves, Aaron Bembenek, Pedro Martins, and Amílcar Cardoso
Proceedings of the 10th International Conference on Computational Creativity (ICCC 2019)
[pdf, bib]
Differential Privacy: A Primer for a Non-Technical Audience
Alexandra Wood, Micah Altman, Aaron Bembenek, Mark Bun, Marco Gaboardi, James Honaker, Kobbi Nissim, David R. O'Brien, Thomas Steinke, and Salil Vadhan
Vanderbilt Journal of Entertainment and Technology Law 21, no. 1 (2018): 209
[pdf, bib]
Bridging the Gap between Computer Science and Legal Approaches to Privacy
Kobbi Nissim, Aaron Bembenek, Alexandra Wood, Mark Bun, Marco Gaboardi, Urs Gasser, David R. O’Brien, and Salil Vadhan
Harvard Journal of Law and Technology 31, no. 2 (2018): 687
Won the Caspar Bowden Award for Outstanding Research in Privacy Enhancing Technologies
[pdf, bib]
AbcDatalog is an open-source implementation of the logic programming language Datalog written in Java. It provides ready-to-use implementations of common Datalog evaluation algorithms, as well as some experimental multi-threaded evaluation engines. It supports language features beyond core Datalog such as explicit (dis-)unification of terms and stratified negation. Additionally, AbcDatalog is designed to be easily extensible with new evaluation engines and new language features.
Privacy Tools Project
From the official website: The Privacy Tools Project is a broad effort to advance a multidisciplinary understanding of data privacy issues and build computational, statistical, legal, and policy tools to help address these issues in a variety of contexts. As part of this project, I contribute to a working group that bridges legal and technical definitions of privacy.

Messenger pigeon is preferred. If your local dovecote is depleted, feel free to email me at . If you are on campus, you can probably find me in Maxwell Dworkin 309.