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Dr Luc Rocher

Departmental Research Lecturer

Dr Luc Rocher

Departmental Research Lecturer

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Luc Rocher is a lecturer in social data science at the Oxford Internet Institute, specialising in large-scale computational modelling approaches to study emerging concerns in algorithmic societies. With training in computer science and computational social science, Luc studies the future of privacy and digital rights as well as the governance of algorithms in digital platforms.

Luc’s research provides technical guidance to the challenges AI poses for competition law in digital platforms and data protection regulation online. Their work in Nature Communications for instance demonstrated the limits of traditional techniques to de-identify and widely share ‘anonymous’ data online, calling for better privacy-preserving frameworks to disseminate and analyse personal data online.

Prior to joining Oxford, Luc received a PhD from the Université catholique de Louvain in 2019 and worked as a researcher at the Data Science Institute and Computational Privacy Group of Imperial College London, at the ENS de Lyon, and at the MIT Media Lab. Their work has been published in peer-reviewed journals and conferences (Nature CommunicationsNature Scientific DataUsenix SecurityJMLRWWW) and is regularly covered in the press (New York TimesThe GuardianThe TelegraphForbesEl PaisScientific American) as well as featured in BBC World Service, France TV, RTBF TV and Radio, Radio Canada. Luc leads the Observatory of Anonymity, an international interactive website in 89 countries where visitors can find out what makes them more vulnerable to re-identification and where researchers can test the anonymity of their research data.

Areas of interest for Doctoral Supervision:

Future of data privacy, competition and regulation of online markets, privacy and anonymity in online platforms, vulnerabilities in socio-technical systems, governance of algorithmic societies, human dynamics, network science, computational social science

Research Interests

Digital privacy, digital rights, machine learning, digital platforms, digital governance.

Positions at the OII

  • Departmental Research Lecturer, October 2021 -


Integrity Statement

I conduct my research in line with the University's academic integrity code of practice.


Current Courses

Fairness, Accountability, and Transparency in Machine Learning

Integrating historical and cultural context with contemporary scholarship, this course equips students with the technical and conceptual tools to engage critically with machine learning research and practice.

Accessing Research Data from the Social Web

This course teaches the essentials of programming in Python, the language of choice in the growing field of computational social science.