Curriculum Vitae
Short Bio
Paavo Sattler is a researcher in statistics working on methodological problems in multivariate, high-dimensional, and nonparametric inference. He is currently a researcher at TU Dortmund University and RWTH Aachen University. His research interests include structured and directional hypotheses, multiple testing, resampling-based methods, covariance and correlation structures, and statistical computing. A recurring theme in his work is the development of methods that connect mathematical questions with practical statistical inference and software implementation.
He received his doctorate in statistics from TU Dortmund University in 2021 with a thesis on inference for multivariate and high-dimensional data in heterogeneous designs. In 2024, he held an interim professorship in Mathematical Statistics at Heidelberg University. His current work includes methodological research, software development, and collaborations in which existing statistical methods can be applied, adapted, or extended to new problems.
Email · ORCID · Google Scholar · GitHub
Research Interests
- Multivariate and high-dimensional statistical inference
- Nonparametric and resampling-based inference
- Structured, multiple, directional, and one-sided hypotheses
- Covariance and correlation structures
- Statistical computing and methodological software
Academic Positions
Since September 2024 — Researcher, TU Dortmund University
Department of Statistics
Since October 2025 — Researcher, RWTH Aachen University
Institute of Statistics and Economic Mathematics
April–August 2024 — Interim Professorship in Mathematical Statistics
Heidelberg University, Faculty of Mathematics and Computer Science
December 2021–March 2024 — Researcher, TU Dortmund University
Department of Statistics
March 2019–October 2021 — Doctoral Researcher, TU Dortmund University
Department of Statistics
September 2016–February 2019 — Doctoral Researcher, Ulm University
Institute of Statistics
Education
2021 — Dr. rer. nat. in Statistics, TU Dortmund University
Inference for multivariate and high-dimensional data in heterogeneous designs
magna cum laude
2016 — M.Sc. in Business Mathematics, Ulm University
High-Dimensional Repeated Measures Analysis: Asymptotics and Multiple Samples
2014 — B.Sc. in Mathematics, University of Stuttgart
Awards & Funding
2026 — DFG Research Grant
Überlegenheit statt bloßer Ungleichheit: Multivariate Inferenz für gerichtete Effekte in der Biostatistik
(Superiority rather than mere inequality: Multivariate inference for directional effects in biostatistics)
Principal investigator · 36 months · planned start July 2027
2018 — Joachim Hartung Prize
Awarded for the presentation Inference for high-dimensional split-plot designs: A unified approach for small to large numbers of factor levels
Teaching & Supervision
Selected Teaching Experience
- Mathematics of Data Science — Master level
- Six Sigma Methods — Master level
- Introduction to Probability Theory and Statistics — Bachelor level
- Seminar in Multivariate Probability and Statistics — Bachelor level
- Reading Course in Statistical Inference — Master level
- Nonparametric Statistics — Master level
Supervision
2024–present — Co-supervision of a PhD project
Semi- and Nonparametric Analysis of Covariance
in collaboration with Prof. Markus Pauly
Selected Bachelor’s Theses
- A Software Package for High-Dimensional Repeated Measures — 2024
- Testing One-Sided Hypotheses Using Quadratic Forms — 2023
- Linear Shrinkage Estimators for High-Dimensional Quadratic-Form Methods — 2022
Academic Service & Activities
2026 — International Workshop: Multivariate and Functional Data Analysis in Biostatistics
Aachen · Co-organized with Dennis Dobler, J. Feifel and M. Munko · Supported by the German Region of the International Biometric Society
2026 — Invited Session: Multiple Tests Beyond Parametric Assumptions
CEN, Warsaw · Organizer
2024 — Session: Inference in the Life and Social Sciences for Small Sample Sizes with Little or No Assumptions
Bernoulli–IMS 11th World Congress, Bochum · Organizer
2024 — Learning Session: Covariate Adjustment in Quantile Regression
Co-organized with M. Baumeister and K. Thiel · Supported by the DMV Young Talent Promotion program
2022 — Summer School “Resampling”
German Region of the International Biometric Society, Strobl · Lecturer
Professional Service
Spokesperson of the Working Group “Nonparametric Methods” of the German Region of the International Biometric Society.
Reviewer for international statistical journals including The R Journal, Metrika, Biometrical Journal, Statistical Papers, Journal of Applied Statistics, and Scandinavian Journal of Statistics.
Software
Publications
See the complete publication list and Google Scholar.