I am a Ph.D. candidate in deep learning at Uppsala University in Sweden. My supervisors are Thomas Schön (main), Niklas Wahlström and Antônio H. Ribeiro. I am fully supported by WASP. My Ph.D. will be finished the summer of 2024.
My research can be split within the field of deep learning in two areas. The applied side revolves around medical problems, where we look at ECG recordings and try to improve the classification of medical conditions with deep learning based models. The theoretical side of my research focuses on understanding how specific deep models works. Specifically, I am interested in unsupervised and self-supervised learning methods and what they are learning from the given data. For details about the results, see my publications.
I received my B.Eng. in Aerospace Engineering from the Baden-Württemberg Corporate State University, Germany in 2015 which was in cooperation with Airbus, Friedrichshafen in Germany. In 2019 I received my M.Sc. degree in Systems and Control from TU Delft in the Netherlands. Between my B.Eng. and M.Sc. degree I have one year of industrial experience in the aerospace industry at Airbus Space. Since 2019 I am pursing my Ph.D. degree.
Latest research results and news
July 25, 2022, Workshop Participation: Next week from 01.08-05.08 I will participate in the Deep Learning Theory Workshop and Summer School at the Simons Institute for the Theory of Computing. This will be my first in-person event since the start of my PhD.
June 02, 2022, Master Defence - Theogene: My master student Theogene Habineza defended his master thesis titled Risk Prediction of Atrial Fibrillation Using the 12-lead ECG. The reviewer was Thomas Schön.
October 26, 2021, Accepted Paper: Our submission to the NeurIPS workshop Machine learning from ground truth: New medical imaging datasets for unsolved medical problems Workshop in ECG classification of myocardial infarctions was accepted as spotlight talk.
Project Paper Slides
All news can be found here