CV
Education
- Ph.D in Mathematical Statistics, University of Copenhagen, 2022 (expected)
- Working on multiple testing, combination testing, causal discovery and invariant causal prediction. Focus on application to high-dimensional datasets.
- MSc in Mathematic-Economics, University of Copenhagen, 2019
- Master thesis: Greedt Learning of Causal Structures in Additive Noise Models.
- BSc in Mathematic-Economics, University of Copenhagen, 2017
Work experience (non teaching)
- Director, JP Statistics ApS, 2019–current
- Research Assistant, University of Copenhagen, 2019
- Student Assistant in Biostatistics, Novo Nordisk, 2017-2019
- Student Assistant in Statistics, Rigshospitale, 2016-2017
- Student Assistant in Accounting, Andersen Accounting and Consultion, 2014-2017
Teaching Experience
- University of Copenhagen:
- Introduction to Mathematics, 2015
- Statistics for Biochemists, 2017 and 2019
- Statistics and Probability, 2016
- Statistical Dataanalysis 2, 2016
- Statistics 2, 2017
- Statistical Dataanalysis 1, 2017
- Measure and Integraltheory, 2017
- Basic Lifeinsurance 1, 2019
- Applied Statistics, 2020 and 2021
- Computational Statistics, 2020 and 2021
- Other
- Tutor in mathematics, physics and chemistry, MentorDanmark, 2014-2017
Programming and software
- Highly experience with:
- Python 3
- R
- SQL
- SAS
- Some experience with:
- VBA
- GAMS
- MatLab
Publications
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values
Weichwald, Sebastian, et al. "Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values." NeurIPS 2019 Competition and Demonstration Track. PMLR, 2020.
Invariant Ancestry Search
Phillip B Mogensen, Nikolaj Thams, Jonas Peters Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15832-15857, 2022.