معرفی
Xavier de Luna is a Professor of Statistics at Umeå School of Business, Economics and Statistics (USBE) at Umeå University in Sweden. He leads the Stat4Reg Lab and is part of the Umeå SIMSAM Lab and the SINGS graduate school. His research focuses on causal inference, machine learning, and statistical methodology applied to social and health sciences. He serves as Editor of the Scandinavian Journal of Statistics (2025-2027) and has held roles as Associate Editor for Biometrics, Computational Statistics and Data Analysis, and Observational Studies.
Education: PhD in Statistics from Swiss Federal Institute of Technology (1996). Prior roles include Head of the Department of Statistics at Umeå University (2009-2011) and affiliation with institutions like IFAU and the Institute of Labour Market Policy Evaluation.
Research interests span causal machine learning, covariate selection, and register-based studies in health and social sciences. Key projects include using generative AI for open science and machine learning for causal discovery. His work addresses challenges like unobserved confounding and high-dimensional data.
Notable contributions include methodological advances in causal inference (e.g., covariate balancing, neural networks for causal effects) and applications in health economics, retirement effects, and brain imaging studies. He has advised over 15 PhD students and secured grants from the Swedish Research Council and Wallenberg Foundation.
Labs/Teams: Stat4Reg Lab (causal inference), Umeå SIMSAM Lab (register-based research), SINGS (interdisciplinary graduate school).
