Yves-Alexandre de Montjoye

Yves-Alexandre de Montjoye is an Assistant Professor (Lecturer) at Imperial College London where he heads the Computational Privacy Group. He is a technical expert appointed by Parliament to the Belgian Data Protection Agency and, in 2018-2019, was a Special Adviser to EC Competition Commissioner Margrethe Vestager. He was previously a postdoctoral researcher at Harvard working with Latanya Sweeney and Gary King and received his PhD from MIT under the supervision of Alex “Sandy” Pentland.

His research aims at understanding how the unicity of human behavior impacts the privacy of individuals—through re-identification or inference—in rich high-dimensional datasets such as mobile phone, credit cards, or browsing data. Yves-Alexandre was recently named an Innovator under 35 for Belgium (TR35). His research has been published in Science and Nature Communications and received wide media coverage ( BBC News, CNN, The New York Times, Wall Street Journal, Harvard Business Review, etc). His work on the shortcomings of anonymization has appeared in reports of the European Commission, World Economic Forum, United Nations, OECD, FTC. Yves-Alexandre worked for the Boston Consulting Group and acted as an expert for both the Bill and Melinda Gates Foundation and the United Nations. He obtained, over a period of 6 years, an M.Sc. from Louvain in Applied Mathematics, a M.Sc. (Centralien) from Ecole Centrale Paris, a M.Sc. from KULeuven in Mathematical Engineering as well as his B.Sc. in engineering at Louvain.


News


Publications

  • Oehmichen, A., Jain, S., Gadotti, A., & de Montjoye, Y. A. (2019) OPAL: High performance platform for large-scale privacy-preserving location data analytics. 2019 IEEE International Conference on Big Data (Big Data) (pp. 1332-1342).
  • Gadotti A., Houssiau F., Rocher L., Livshits B., de Montjoye Y. A. (2019) When the signal is in the noise: Exploiting Diffix's Sticky Noise. 28th USENIX Security Symposium (USENIX Security 19).
    Selected Press: TechCrunch, Wall Street Journal
  • Rocher, L., Hendrickx, J. M., & de Montjoye, Y. A. (2019) Estimating the success of re-identifications in incomplete datasets using generative models. Nature communications, 10 (1), 3069.
    Selected Press: New York Times, Guardian, CNBC, The Telegraph, TechCrunch, Technology Review, New Scientist, Gizmodo, Scientific American, RT, Forbes, El Pais (ES), Sueddeutsche Zeitung (DE), Le Soir (FR), La Libre (FR), L'Echo (FR), De Morgen (NL)
  • Schellekens V., Chatalic A., Houssiau F., de Montjoye Y. A., Jacques L., Gribonval R. (2019) Differentially Private Compressive K-means. ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
  • Jain, S., Bensaid, E., & de Montjoye, Y. A. (2019) UNVEIL: Capture and Visualise WiFi Data Leakages. The World Wide Web Conference (pp. 3550-3554).
  • Houssiau F., Radaelli L., Sapiezynsky P., Shmueli E., de Montjoye Y. A. (2018) Quantifying surveillance in the networked age: Node-based intrusions and group privacy. .
  • de Montjoye Y. A., Farzanehfar A., Hendrickx J., Rocher L. (2017) Solving Articifical Intelligence's Privacy Problem. Field Actions Science Reports. The journal of field actions (Special Issue 17) pp 80-83.