I am a Ph.D. candidate at Uppsala University, Sweden advised by Thomas Schön (main), Niklas Wahlström and Antônio H. Ribeiro. I am fully supported by WASP.

In my research I try to understand deep learning through theory and empirical observations. I am interested in

On the applied side, my research uses deep models for the evaluation of electrocardiogram (ECG) recordings to (1) support physicians with diagnosis and (2) explore the information within those recordings.


Latest research results and news

November 6, 2023, Accepted Paper: The first work from my research visit at Misha Belkins Lab at UCSD was accepted at the UniReps workshop at NeurIPS. We studied the emergence of similar representations in Recursive Feature Machines and in GPs with Automatic Relevance Determination.
OpenReview NeurIPS23 workshop

September 30, 2023, Accepted Paper: Our MSc students work on ECG-based risk prediction was published at the Journal of Electrocardiography. Congrats, Theogene!
doi arXiv code models

July 4, 2023, Accepted Paper: Another work ours using ECGs + deep learning got accepted at PLOS Neglected Tropical Diseases. We show that deep learning models can be used to detect Chagas disease from ECGs, aiding in early detection.
doi medRxiv code models

June 28, 2023, Invited Talk: A talk on our preprint survey paper of deep networks for system identification got accepted at the 2023 European Research Network System Identification (ERNSI) workshop in Stockholm. We got a special 1h presentation slot.
workshop arXiv

All news can be found here