Presented By O'Reilly and Cloudera
Make Data Work
December 1–3, 2015 • Singapore
Yves-Alexandre de Montjoye

Yves-Alexandre de Montjoye
Lecturer | Research Scientist, Imperial College London | MIT Media Lab

Website | @yvesalexandre

Yves-Alexandre de Montjoye is a lecturer at Imperial College London, a research scientist at the MIT Media Lab, and a postdoctoral researcher at Harvard IQSS. His research aims to understand how the unicity of human behavior impacts the privacy of individuals—through reidentification or inference—in large-scale metadata datasets such as mobile phone, credit cards, or browsing data. Previously, he was a researcher at the Santa Fe Institute in New Mexico, worked for the Boston Consulting Group, and acted as an expert for both the Bill and Melinda Gates Foundation and the United Nations. Yves-Alexandre was recently named an innovator under 35 for Belgium. His research has been published in Science and Nature Scientific Reports and has been covered by the BBC, CNN, the New York Times, the Wall Street Journal, Harvard Business Review, Le Monde, Die Spiegel, Die Zeit, and El Pais as well as in his TEDx talks. His work on the shortcomings of anonymization has appeared in reports of the World Economic Forum, United Nations, OECD, FTC, and the European Commission. He is a member of the OECD Advisory Group on Health Data Governance. Yves-Alexandre holds a PhD in computational privacy from MIT, an MSc in applied mathematics from Louvain, an MSc (centralien) from École Centrale Paris, an MSc in mathematical engineering from KU Leuven, and a BSc in engineering from Louvain.


11:50am–12:30pm Thursday, 12/03/2015
Security & Governance
Location: 334-335 Level: Non-technical
Yves-Alexandre de Montjoye (Imperial College London | MIT Media Lab)
Average rating: ****.
(4.83, 12 ratings)
We're living in an age of big data, a time when metadata about most of our movements and actions are collected and stored in real time. These data offer unprecedented insights on how we behave. Mathematical analysis of metadata, however, reveals how unique our behavior is and how this behavior puts fundamental constraints on our privacy. Read more.