2021
  1. Privacy Policies over Time: Curation and Analysis of a Million-Document Dataset R. Amos, G. Acar, E. Lucherini, M. Kshirsagar, A. Narayanan, and J. Mayer Proceedings of The Web Conference (WWW) 2021 ✨ More than 80 data access requests [arXiv] [web] [code]
  2. Adapting Security Warnings to Counter Online Disinformation B. Kaiser, J. Wei, E. Lucherini, K. Lee, J. Matias, and J. Mayer In 30th USENIX Security Symposium (USENIX Security) 2021 [arXiv]
  3. T-RECS: A simulation tool to study the societal impact of recommender systems E. Lucherini, M. Sun, A. Winecoff, and A. Narayanan arXiv preprint arXiv:2107.08959 2021 [arXiv] [code]
  4. Simulation as Experiment: An Empirical Critique of Simulation Research on Recommender Systems A. Winecoff, M. Sun, E. Lucherini, and A. Narayanan arXiv preprint arXiv:2107.14333 2021 [arXiv]
2020
  1. T-RECS: A General Simulation Tool to Study the Impact of Recommendation Systems E. Lucherini, M. Sun, and A. Narayanan 15th Women in Machine Learning Workshop (WiML) 2020 [poster]
2019
  1. Dark Patterns at Scale: Findings from a Crawl of 11K Shopping Websites A. Mathur, G. Acar, M. Friedman, E. Lucherini, J. Mayer, M. Chetty, and A. Narayanan ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) 2019 ✨ FPF’s 2019 Privacy Papers for Policymakers Award [arXiv] [web]
  2. Investigating sources of PII used in Facebook’s targeted advertising G. Venkatadri, E. Lucherini, P. Sapiezynski, and A. Mislove In Proceedings on Privacy Enhancing Technologies 2019 ✨ Best Student Paper Award [pdf]
2017
  1. Design and Implementation of a Memory Allocator to Achieve Cache Partitioning in the Linux Kernel E. Lucherini Master's Thesis 2017