Mathias Drton
Affiliated Professor of Statistics and Data Science
Research Interests
Professor Drton's teaching and research interests span probabilistic graphical models, causal inference, singular learning theory, and algebraic statistics.
Email
In addition to his position at MBZUAI, Professor Drton is Professor of Mathematical Statistics at the Technical University of Munich, Germany. He holds a Ph.D. in Statistics from the University of Washington (2004) and has held faculty positions at the University of Copenhagen (2018-19), the University of Washington (2012-2019), and the University of Chicago (2005-2012).
- Ph.D. in Statistics, University of Washington, Seattle, USA
- Diploma in Applied Mathematics, Universität Augsburg, Germany
- Diplôme d'Études Approfondies in Applied Mathematics, Université Toulouse III Paul Sabatier, France
- ERC Advanced Grant, European Research Council, 2020
- Elected Member, International Statistical Institute, 2020
- Ethel Newbold Prize, Bernoulli Society, 2019
- Elected Foreign Member of the Royal Danish Academy of Sciences and Letters, 2018
- Fellow of the Institute of Mathematical Statistics (IMS), 2016
- Medallion Lecture, Institute of Mathematical Statistics (IMS), 2014
- Mathias Drton, Daniele Tramontano, and Jalal Etesami: "Parameter identification in linear non-Gaussian causal models under general confounding", The Annals of Statistics, 54, no. 2: 957–981, 2026.
- Mathias Drton, Y. Samuel Wang, and Mladen Kolar: "Confidence Sets for Causal Orderings", Journal of the American Statistical Association, 121, no. 553: 690–703, 2025.
- Mathias Drton and Daniela Schkoda: "Goodness-of-fit tests for linear non-Gaussian structural equation models", Biometrika, 112, no. 4, asaf046, 2025.
- Mathias Drton, Nils Sturma, and Dennis Leung: "Testing many constraints in possibly irregular models using incomplete U-statistics", Journal of the Royal Statistical Society Series B: Statistical Methodology, 86, no. 4: 987–1012, 2024.
- Mathias Drton and Y. Samuel Wang: "Causal Discovery with Unobserved Confounding and Non-Gaussian Data", Journal of Machine Learning Research, 24, paper no. 271: 1–61, 2023.
- Mathias Drton, Philippp Dettling, Roser Homs, Carlos Améndola, and Niels Richard Hansen: "Identifiability in Continuous Lyapunov Models", SIAM Journal on Matrix Analysis and Applications, 44, no. 4: 1799–1821, 2023.