Andrea Gadotti

Email: [my_surname] AT

I’m a PhD student in the Computational Privacy Group at Imperial College London. My work focuses on privacy-enhancing technologies, and specifically on finding vulnerabilities in query-based systems designed for the analysis of personal data. I also work on OPAL (Open Algorithms), a collaborative project with involvement from Orange, Telefonica, and MIT, to enable the use of mobile phone data in a safe and ethical manner.

Before my work in privacy, I received a BSc in Math from the University of Trento and a MSc in Mathematical Logic from the University of Turin. I spent one year at the Graz University of Technology as an Erasmus student and six months at the University of Vienna. My personal interests lie at the intersection between policy and technology for digital rights such as privacy, freedom of expression online and open knowledge.



  • Gadotti A., Houssiau F., Annamalai M.S.M.S., & de Montjoye, Y. A. Pool Inference Attacks on Local Differential Privacy: Quantifying the Privacy Guarantees of Apple's Count Mean Sketch in Practice. 31st USENIX Security Symposium (2022).
  • Oehmichen, A., Jain, S., Gadotti, A., & de Montjoye, Y. A. OPAL: High performance platform for large-scale privacy-preserving location data analytics. 2019 IEEE International Conference on Big Data (Big Data) (pp. 1332-1342) (2019).
  • Gadotti A., Houssiau F., Rocher L., Livshits B., de Montjoye Y. A. When the signal is in the noise: Exploiting Diffix's Sticky Noise. 28th USENIX Security Symposium (2019).
    Selected Press: TechCrunch, Wall Street Journal