I am a postdoctoral researcher at the Tübingen AI center at the University of Tübingen, Germany working with Jakob Macke.

My research is fairly diverse. Mainly, I try to understand deep learning through theory and empirical observations to then apply it to solve scientific problems. Specifically, I am interested in

On the applied side, I develop deep models for (1) automated evaluations of electrocardiogram (ECG) recordings, and (2) for systems pharmacology models, with focus on chronic kidney disease.


Background


Latest research results and news

September 15, 2024, Postdoc: I started my postdoc at the Tübingen AI center at the University of Tübingen, Germany.

June 14, 2024, Ph.D.: I successfully defended my Ph.D. thesis “On Deep Learning for Low-Dimensional Representations”.
pdf DiVA slides

May 2, 2024, Accepted Paper: Our high-dimensional analysis paper got accepted to ICML. We study the combination of Principal Component Analysis (PCA) with linear regression on data from a spiked covariance model to provide precise asymptotic guarantees for the risk.
OpenReview ICML code poster

April 26, 2024, Accepted Paper: Our work on integrating Recursive Feature Machines (RFMs) into Gaussian Processes was accepted at UAI. We show that the resulting GP-RFM is a strong alternative to existing SOTA methods for tabular regression problems.
OpenReview code poster

All news can be found here