Hey, I’m Laura!

I’m a PhD student in mathematical statistics at Humboldt-Universität zu Berlin, supervised by Markus Reiß and funded by Project 2 of the DFG research unit FOR 5381 – Mathematical Statistics in the Information Age.

My research focuses on iterative algorithms, particularly (conjugate) gradient methods for statistical inverse problems, with an emphasis on early stopping to achieve both statistical accuracy and computational efficiency. I’m also interested in the spectral properties of high-dimensional random matrices, a passion that began with my Master’s thesis under the supervision of Martin Wahl and continued in my work on principal component regression.

I enjoy connecting mathematical theory with practical statistical applications, exploring how theoretical insights can improve real-world algorithms. Feel free to contact me to discuss research ideas, collaborations, or questions about early stopping, iterative methods or spectral analysis.