About me

I'm Assistant Professor at Uppsala University in Sweden. My work studies techniques to extract information and learn the intrinsic behavior of time series, signals and dynamical systems. I have a focus on large-scale models that can perform such tasks, with a special interest in their robustness and generalization capabilities. While motivated by a range of applications, I am particularly interested in the new prospects these advances can bring to medicine. In particular cardiology and electrocardiography.

Contact

Uppsala University
Department of Information Technology
Ångströmslaboratoriet, Hus 10, Room 103179

Postal address: Box 337, 751 05, Uppsala, Sweden.
Email: antonio.horta.ribeiro@it.uu.se

News

2023-07-19 📜 New paper at ICML. We provide a high-dimensional analysis of PCA + Linear regression (PCR). (link)
2023-06-25 📜 Two new papers: npj Digital Medicine and Scietific Reports. AI-ECG for predicting electrolytes and cardiometabolic disease. (link) (link)
2023-06-14 🎓 Daniel Gedon successfully defended his PhD thesis. His thesis include publications on ICML, UAI, Scientific Reports and IEEE Signal Processing Letters. Next he is going to Tübingen University, Germany, as a PostDoc. (link)
2023-06-05 📜 New paper about generalization of deep learning in AI-ECG. (link)
2023-06-01 👨🏻‍🏫 I started as Assistant Professor at Uppsala University (link)
2023-05-31 🎓 Arvid Eriksson successfully defended his MSc thesis. His master thesis generated a paper that will be presented in Computer in Cardiology 2024. He also got a position at KTH as a PhD Student. (link)
2023-02-20 🎬 Talk at Karolinska as part of DDLS fellows program. (link)
2023-02-19 📜 New paper about knowledge discovery in AI-ECG accepted in EHJ Digital Health (link)
2023-02-01 ✈️ I started as postdoctoral researcher at KTH Royal Institute of Technology, Sweden, (link)
2023-10-30 🎬 I present my work in the seminar series from the National Laboratory of Scientific Computing (Brazil) (link)
2023-10-05 📜 New paper accepted at NeurIPS as a spotlight. (link)
2023-10-01 📜 New publications at Journal of Electrocardiology: Risk Prediction of Atrial Fibrillation from the 12-Lead ECG by a Deep neural network. (link)
2023-09-25 🎬 I presented my work on the European Research Network System Identification (ENRSI) workshop in Stockholm (link)
2023-07-27 📜 Two new publications: one at Circulation and one at the European Heart Journal Digital Health. (link) (link)
2023-07-05 ✈️ I visited Fu Siong group at Imperial college for one week. (link) (link)
2023-07-04 📜 Two new publications using AI-augmented ECG: screening for Chagas disease patients and using age estimated by AI-ECG as a biomarker of cardiovascular risk (link) (link)
2023-05-24 🎬 Two online talks today. One at PUC-Rio-Brazil and one at IEEE EMBS Germany Chapter in Göttingen!. (link) (link)
2023-05-12 📜 Paper accepted at IEEE Signal Processing Letters. Invertible Kernel PCA with Random Fourier Features (link)
2023-04-04 📜 Paper accepted at Frontiers in Cardiovascular Medicine. Association of lifestyle with deep-learning based ECG-age (link)
2023-02-15 📜 Paper accepted at IEEE Transactions on Signal Processing. Overparameterized Linear Regression under Adversarial Attacks (link)
2023-01-25 📜 Paper accepted at IEEE Transactions on Biomedical Engineering. On Merging Feature Engineering and Deep Learning (link)
2022-11-25 ✈️ I was awarded the ELISE Mobility Grant for a research visit to Francis Bach group at ENS/INRIA during Spring 2023.
2022-11-24 🎬 Talk at Aalto University and ELLIS unit Helsinki! "Adversarial Attacks in Linear Regression". (link)
2022-11-15 📜 Paper accepted at Scientific Reports. Deep learning ECG-based prediction of myocardial infarction (link)
2022-08-15 🏆 I received the Benzelius Award! From the Royal Academy of Sciences in Uppsala (photo)
2022-06-29 🎓 Theogene Habineza successfully defended his MSc thesis. His master thesis generated a paper accepted for publication in Journal of Electrocadiography. (link) (link)