معرفی
Dominik Rothenhäusler is an Assistant Professor of Statistics at Stanford University, holding the position since September 1, 2019. He serves as a David Huntington Faculty Scholar and Chamber Fellow, with his office located in CoDa E222 at Sequoia Hall.
He earned his PhD in Mathematics from ETH Zurich in Summer 2018 under Nicolai Meinshausen and Peter Bühlmann, receiving the ETH medal for outstanding doctoral thesis. Prior to Stanford, he completed a postdoctoral fellowship with Bin Yu at UC Berkeley.
Rothenhäusler's research centers on causal inference, distribution shift, and replicability, developing methods for statistical validity under data distribution changes. He addresses challenges in high-dimensional statistics and heterogeneous data where traditional uncertainty measures fail, aiming to improve prediction reliability and feature selection replicability through innovations in graphical models and distributional robustness.
His recent work reveals critical trends in distribution shift research, including frameworks for random dense shifts, diagnostic tools for replication failures, and modular inference systems. Publications span top venues like NeurIPS, Biometrika, and JMLR, emphasizing practical applications for real-world data stability and causal evidence integration.
Key recognition includes:
- David Cox Research Prize by the Royal Statistical Society (2022)
Supported by the Dieter Schwarz Foundation, Chamber Foundation, and David Huntington Fellowship, his research program focuses on robust statistical methodology development. While student names aren't specified in source materials, he actively advises graduate researchers within Stanford's Statistics Department.
Rothenhäusler collaborates with Stanford's AFT Laboratory (evidenced by Spring 2024 seminar), forming interdisciplinary teams tackling distributional challenges in causal inference. His work integrates theoretical statistics with machine learning applications across healthcare, social sciences, and industrial analytics domains.
