My research focuses on the sociology of finance (particularly, automated trading), new techologies (including machine learning and quantum computing), urban sociology and architecture, as well as social theory (crowd theory, Tarde, Luhmann, postcolonial theory, etc.).
My earlier work had a leaning toward criminology, urban sociology, and historical sociology/sociology of knowledge, as manifested in my award-winning book, The Politics of Crowds: An Alternative History of Sociology (Cambridge UP, 2012). During the past decade, I have been studying financial markets with a particular focus on the ways in which the deployment of fully automated trading algorithms is transforming securities trading. I have pursued work on this topic as the PI of two large interdisciplinary research projects, a Sapere Aude project funded by the Independent Research Fund Denmark and a Consolidator project funded by the European Research Council. Under the auspecies of these projects, I did extensive qualitative fieldwork, interviewing traders, regulators, developers, and other market participants working in financial hubs such as London, New York, and Chicago. In addition to the qualitative fieldwork, I am working with colleagues on developing agent-based simulations of interactions among algorithms in the financial markets. Ongoing work on this topic includes collaboration with computer scientists specializing in natural language processing (research that is funded by a grant from the Villum Foundation).
I am currently working on two books: The Oxford Handbook of the Sociology of Machine Learning (Oxford University Press, 2023/4; ed. with Juan Pablo Pardo-Guerra) and Making Autonomous Markets: How Machine Learning is Reshaping Financial Markets (under contract with Stanford University Press). The latter volume complements my most recent book, Social Avalanche: Crowds, Cities and Financial Markets (Cambridge UP, 2020), by examining the uptake of machine learning technologies in financial markets.