I’m a first year ELLIS PhD student at the Amsterdam Machine Learning Lab supervised by Eric Nalisnick and Dan Zhang. My PhD research focuses on out-of-distribution detection and generalization. Previously, I wrote my Master’s thesis on continuous-time modeling under the supervision of Maja Rudolph at the Bosch Center for Artificial Intelligence. I’m also a machine learning consultant at the World Bank where I work with Sam Fraiberger on inferring causal relations from development economics literature.
I graduated with a joint Master’s in statistics from the Technical University Berlin and Humboldt University Berlin and hold a French engineering degree in applied mathematics and economics from ENSAE. In my Bachelor’s, I studied Economics and Political Science at Humboldt University Berlin and the University of Munich.
Schirmer, M., Eltayeb, M., Lessmann, S., & Rudolph, M. (2022, June). Modeling irregular time series with continuous recurrent units. In International Conference on Machine Learning (pp. 19388-19405). PMLR. [Paper]
Schirmer, M., Eltayeb, M., & Rudolph, M. (2021, September). Continuous-Discrete Recurrent Kalman Networks for Irregular Time Series. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases (pp. 300-305). Springer, Cham. [Workshop Paper]