• Machine Learning for finance
• (Self-similar) stochastic processes (e.g., interacting particle systems)
• Statistics for stochastic processes

Heinrich-Heine-University

• Tutorials in "Financial Mathematics I" (Spring 2024)
• Tutorials in "Probability Theory" (Fall 2023)

Technical University of Dortmund (as an undergraduate and PhD student)

• Tutorials in "Stochastic Analysis with application in Financial Mathematics" (Spring 2018, Spring 2023)
• Tutorials in "Lévy processes and option pricing" (Fall 2018)
• Tutorials in "Stochastic I" (Spring 2015, Spring 2016, Spring 2022)
• Tutorials in "Stochastic II" (Fall 2015, Fall 2016, Fall 2022)
• Tutorials in "Analysis I" (Fall 2014)
• Tutorials in "Analysis II" (Fall 2016, Fall 2019)

Submitted for publication:

1. Hufnagel N. and Andraus S. (2023+): Collision times of multivariate Bessel processes with their Weyl chambers' boundaries and their Hausdorff dimension.
   https://arxiv.org/abs/2312.05420
2. Hufnagel N. and Andraus S. (2021+): Hausdorff dimension of collision times in one-dimensional log-gases.
   https://arxiv.org/abs/2109.08707

Peer-reviewed journals:

1. Cheng Y., Hufnagel N. and Masuda H. (2022): Estimation of ergodic square-root diffusion under high-frequency sampling. Econometrics and Statistics
   https://doi.org/10.1016/j.ecosta.2022.05.003
2. Hufnagel N. and Woerner J.H.C. (2022): Martingale estimation functions for Bessel processes. Statistical Inference for Stochastic Processes, Vol. 25, 337-353
   https://link.springer.com/article/10.1007/s11203-021-09250-8