Francis Lee is an Associate Professor at Södertörn University, Media Technology and Chalmers University of Technology at the Division of Media Technology and the Division for Science, Technology, and Society. His research examines how digital technologies—such as algorithms, artificial intelligence, and big data infrastructures—shape our understanding of the world.

You can find his personal webpage here: https://francislee.org. External link.

Research Focus

Lee's research is grounded in the tradition of Science and Technology Studies (STS), focusing on how technologies shape how we classify, value, and understand society. Drawing on STS perspectives that emphasize the co-production of technology and the social order, his work investigates how technologies become intertwined with knowledge production. His current projects explore how artificial intelligence and big data are reshaping biomedical research practices and knowledge production.

Research Projects

A New Scientific Revolution? Consequences of AI and Big Data in Biomedicine Funded by Marianne och Marcus Wallenbergs Stiftelse. This project examines how human judgment and traditional scientific methods in biomedical research are being supplemented and sometimes replaced by data-driven and algorithmic analysis of large datasets.

Social Complexity and Fairness in Synthetic Medical Data. This WASP-HS funded project investigates how synthetic data is intertwined with overlapping social identities such as race, gender, and class, with particular focus on ethical implications for medical applications.

The Rise of Infodemiology Principal Investigator for this Swedish Research Council funded project that investigated how new computational tools and data infrastructures reshape society's understanding of disease risks and outbreaks.

Universal Ambitions of Computation Principal Investigator for this Riksbankens Jubileumsfond funded network that examines how algorithms travel between different areas of society, and how they translate ways of classifying and valuing people between domains.

Algorithms as Devices of Power and Valuation Principal Investigator for this network grant from Riksbankens Jubileumsfond, which established an international research network focused on the social study of algorithms.

Trials of Value Co-applicant on this Riksbankens Jubileumsfond funded project that examined valuation practices in designing medical experiments.

Leadership Roles

Lee serves on the management team for The Wallenberg AI, Autonomous Systems and Software Program – Humanities and Society (WASP-HS), where he contributes to strategic decision-making and shapes the future direction of this national research program.

He is also a board member of the European Association for the Study of Science and Technology (EASST) as of 2025, and heads the Digital STS Hub at Chalmers University. He is also Associate Editor for the peer-reviewed journal Valuation Studies.

Academic Background

Associate Professor Lee holds a PhD in Technology and Social Change from Linköping University (2010) and received his Docent qualification (Associate Professor) in 2016. His academic journey spans multiple institutions, including positions at Uppsala University, Linköping University, and visiting fellowships at institutions like the Centre de Sociologie de l'Innovation at École nationale supérieure des mines de Paris and Lancaster University.

Research Approach

Methodologically, Lee employs an approach that examines how technologies fold heterogeneous elements together, paying attention to how different modes of sensing, calculating, and valuing are coordinated in practice. His work spans theoretical development and empirical investigation, using methods from ethnography, document analysis, and interviews to understand how technologies are intertwined with knowledge production.

Teaching and Mentorship

Lee is an experienced educator who has taught at all academic levels—from undergraduate to doctoral—in courses ranging from intimate seminars to lectures with hundreds of students. His teaching emphasizes interactive and embodied approaches to learning, including activities such as the "Algorithm Walk" and "Epistemic Black Boxes" that help students develop critical thinking skills through experience.

As a supervisor, he has guided multiple PhD students to successful completion of their dissertations and currently supervises doctoral research in emerging areas like AI applications at NASA and the ethics of synthetic medical data.