Luc Rocher is the Director of the DPhil Programme in Social Data Science and is a lecturer at the Oxford Internet Institute. Luc is a fellow at Kellogg College and at Imperial College London’s Data Science Institute.
Their research investigates the harms posed by large-scale collections of digital human traces—from social media traces to biometrics—and deployed artificial intelligence technologies, identifying gaps in how technology is regulated and how risks are documented, and proposing better models for academic research using sensitive human data.
Luc specialises in computational modelling approaches to study emerging concerns in algorithmic societies, such as the future of privacy and digital rights as well as the governance of algorithms in digital platforms. Their research develops statistical models to make sense of these complex systems, adversarial machine learning approaches to highlight weaknesses of deployed technologies, and interactive tools for everyone to better understand what makes them more vulnerable to privacy harms online.
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 Communications, Nature Machine Intelligence, Nature Scientific Data, Usenix Security, JMLR, WWW) and has been covered by 160+ newspapers (New York Times, The Guardian, The Telegraph, Forbes, El Pais, Scientific American) as well as featured in John Oliver’s Last Week Tonight, BBC World Service, France TV, and Radio Canada. Their research on the limitation of anonymisation practices has been referenced by the European Commission, OECD, World Bank, WEF, FTC, by European data protection authorities, in US legal cases, and led to changes to the UK’s Data Protection Bill.
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.
Pronouns: they/them.
I am looking for motivated students interested in studying the impact of privacy-enhancing technologies and auditing algorithms used by public institutions and online platforms. Interest in mathematical modelling and complex systems appreciated (including bayesian statistics, optimisation, network science, machine learning, Python/Julia programming).
In the past five years, my work has been financially supported by UK and Belgian taxpayers, by the Engineering and Physical Sciences Research Council (EPSRC), Innovate UK, the Information Commissioner’s Office (ICO), the John Fell Fund from Oxford University Press, and the Belgian National Fund for Scientific Research (F.R.S.-FNRS).
I conduct my research in line with the University's academic integrity code of practice.
8 June 2023
Experts from the Oxford Internet Institute (OII) are calling for better access to platform data for academic and civil society research, in order to understand the impact of platform algorithms
4 May 2023
Sophisticated computer algorithms used to set prices in online marketplaces put consumers at risk of collusion among sellers, according to a study today from computer scientists at the Oxford Internet Institute and Imperial College.
29 November 2022
Having given expert evidence on the risks of using data proxies for bias monitoring at a workshop hosted by the Centre for Data and Ethics Innovation (CDEI) at the Department for Digital, Culture, Media & Sport. Dr Luc Rocher shares their insights.
DPhil Student
Andrew holds a B.S. in Applied Mathematics from Yale University and an MSc in Social Data Science from the OII. He is a Clarendon Scholar and was previously a Thouron Prize winner at the University of Cambridge (Pembroke College).
DPhil Student
Lujain is a DPhil student in Social Data Science at the OII. Her research sits at the intersection of AI governance and human-centred computing, particularly examining how user autonomy and control are undermined in human-AI interactions.
DPhil Student
Juliette's research interests lie within Human-Centred Data Science, algorithmic bias and social justice.
DPhil Student
Manuel is a DPhil student in Social Data Science. He is broadly interested in using Natural Language Processing to extract policy-relevant information from social media data.
Former MSc Student
Eglė was a Shirley Scholar at the Oxford Internet Institute. She holds a degree in Political Science with a minor in Economics from New York University Abu Dhabi.
Former MSc Student
Sydney Kessler holds a BS in Cognitive Science from UC San Diego. Formally a research associate in computational neuroscience, Sydney is especially interested in using AI, NLP, and data scraping as a means of studying social media subcultures.
Former MSc Student
Kaley is an MSc in Social Data Science student at the OII. She is passionate about research and education on systems of oppression. Kaley holds a BS in Criminology and previously worked in crime analysis.
Former MSc Student
Adriano uses data science in human rights investigations. He is a journalist, educator and researcher with a master's degree in Communication from the Federal University of Rio de Janeiro.
Former MSc Student
Asanilta Fahda holds a BSc in Informatics/Computer Science and worked for 5 years as a software engineer in several international companies ranging from e-commerce, data analytics, to FP&A software. She joined the OII as a Jardine Scholar.
Former MSc Student
Ariana is interested in the social impact of technology. She previously worked as a product consultant for an asset management firm and holds a BA in Information Science and Sociology from Cornell University.
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.
This course teaches the essentials of programming in Python, using the language to access data from a diverse variety of sources on the social web, and transforming this material into datasets which are amenable to traditional social science analysis.
This course teaches the essentials of programming in Python, the language of choice in the growing field of computational social science.
