I am a PhD student in mathematics at the Universiteit Twente. My current work focuses on the theoretical analysis of machine learning methods, in particular gradient descent training with added algorithmic noise. Typically, the problems involve non- asymptotic analysis of such algorithms and their statistical optimality. Previously, I worked on Bayesian variational inference.

Apart from my main research topics, I am interested in applications of differential and metric geometry, optimal transport, and functional analysis in probability and statistics. I keep up to date with relevant developments and try to find connections between these fields in my own work.

Feel free to contact me if you want to discuss anything, or simply talk about mathematics!

Upcoming Talks and Attendances

15th Workshop on Stochastic Models, Statistics and Their Applications (SMSA 2024)
51st Stochastics Meeting Lunteren
AI & Mathematics PhD Networking Event
Seminar of Statistics & Operations Research (UoA)
Mathematics and Data Science Seminar (UTwente)

Recent Publications

(2023). Dropout Versus $\ell_2$-Penalization in the Linear Model. ArXiv Preprint.


(2021). sparsevb: Spike-and-Slab Variational Bayes for Linear and Logistic Regression. The Comprehensive R Archive Network.


(2020). Spike and slab variational Bayes for high dimensional logistic regression. Advances in Neural Information Processing Systems 33.

NeurIPS ArXiv


PhD in Mathematics
September 2021 – Present The Netherlands
MSc in Mathematics
September 2018 – August 2021 The Netherlands
  • Thesis: Sparse Variational Inference and Bayesian High-Dimensional Regression
  • Supervisor: Botond Szabó
BSc in Mathematics
September 2014 – May 2018 United States of America


  • g "dot" clara "at" utwente "dot" nl
  • Zilverling, Hallenweg 19, 7522 NH Enschede, The Netherlands