Most of my career has been spent in the U.S. and Canada, but I feel fortunate to have held positions across the world — China, France, the U.S., Canada, Haïti, and now Japan — and to have been part of institutions that helped me develop: the Salzburg Global Seminar, Harvard, ZBW-Leibniz. Learning, growing and meeting different cultures in this transformative time is what I really like.
My research trajectory has progressively shifted from conventional econometric analysis toward computationally intensive explorations of economic complexity. Rooted in early work on fiscal integration and monetary union, it now integrates network theory, natural-language processing, geospatial data science (geoAI) and machine learning to read the roughly ninety percent of the world’s information that is unstructured — asking how information flows, algorithmic coordination and technological change reshape economic and social systems, and where the world is heading. Throughout, I have sought to make methodological innovation endogenous to inquiry, developing reproducible toolkits such as metadata-driven systematic reviews and domain-specific R packages.
Since June 2026 I have been a Resident Fellow at NICT — Japan’s National Institute of Information and Communications Technology — in Tokyo, working on multilingualism and multiculturalism in AI, a thread that also runs through my forthcoming book Japan in Transition.
I am a signatory of DORA, the San Francisco Declaration on Research Assessment: research should be judged on its own merits rather than by the impact factor of the journal that carries it, and datasets and software deserve to count as first-class scholarly outputs — a conviction reflected in the open R packages and reproducible pipelines that sit alongside my articles.
I am a graduate of the Harvard Business Analytics Program and earned my Ph.D. in Financial Economics from ESSEC Business School in Paris.