Antônio H. Ribeiro

Antônio H. Ribeiro

Assistant Professor at Uppsala University
Department of Information Technology

My goal is to understand and learn from signals and dynamical systems, building AI methods that meet the standards of evidence required in medicine.

Explore my research Curriculum vitae (PDF)
Antônio H. Ribeiro
Uppsala University
Sweden

About my work

My research brings together machine learning, automatic control, and signal processing. I work on the development of techniques to extract information and learn the intrinsic behavior of time series, signals, and dynamical systems, with a focus on large-scale models and their robustness and generalization. I am particularly interested in what these advances can bring to medicine, especially cardiology and electrocardiography.

  • Double descent learning curve Learning & robustness

    Understanding generalization and reliability of large-scale models from first principles.

  • Electrocardiogram signal Signals & systems

    Building tools for time series, system identification, and learning dynamics.

  • Connected telehealth network AI for medicine

    Deploying advanced AI models in medical pipelines.

News & updates

  1. 📜 Our paper "Anytime-Valid Conformal Risk Control", with Bror Hultberg and Dave Zachariah, has been accepted at NeurIPS 2026. Read more ↗

  2. 📝 I will teach Learning Theory and High-Dimensional Statistics at Uppsala University from January to March 2027. Course details and registration are now available. Read more ↗

  3. 📜 Our journal paper on the George B. Moody PhysioNet Challenge 2025 is now published in Physiological Measurement. We report on detecting Chagas disease from the ECG. Read more ↗

  4. Group photo at the launch of ELLIS Unit Sweden at KTH.
    ELLIS Unit Sweden launch, 15 October 2026. Photo: Christer Gummesson.

    🎬 ELLIS Unit Sweden was inaugurated, bringing together researchers from KTH, Uppsala University, Linköping University, and Chalmers. Read more ↗

  5. 📜 New paper in Expert Systems with Applications. We improve interpretability and feature attribution in hybrid AI-ECG models by controlling metadata leakage and feature interactions. Read more ↗

  6. 📜 New paper in PLOS Digital Health. We investigate how pretraining data composition affects the performance and generalisation of ECG foundation models, and propose a strategy to improve transfer to unseen populations. Read more ↗

Earlier updates

  1. 👨🏻‍🏫 I joined the Editorial Board of PLOS Digital Health as an Academic Editor. Read more ↗

  2. 🏆 Our paper "Deep networks for system identification: A survey" received the 2026 Automatica Paper Prize Award from IFAC. Read more ↗

  3. 📜 New paper in Circulation. Opportunistic Screening for Chagas Disease Using an Artificial Intelligence-Enabled ECG: Prospective Evaluation of Feasibility and Diagnostic Accuracy. Read more ↗

  4. 📜 New paper at IEEE Transactions on Biomedical Engineering. Explaining deep learning for ECG using time-localized clusters. Read more ↗

  5. 📜 New paper at Nature Communications. A deep learning ECG model for localization of occlusion myocardial infarction. Read more ↗

  6. 📜 New paper at npj Digital Medicine. CODE-II: A large-scale dataset for artificial intelligence in ECG analysis. Read more ↗

  7. 🏆 I was awarded a WASP Academic PhD Project grant. The project is titled: "Large-Scale Robust Machine Learning via Minmax Formulations".

  8. February 2026 cover of Nature Machine Intelligence featuring a foundation model for cardiac health monitoring.

    📜 New paper at Nature Machine on fondation models for health monitoring is the cover of February issue Read more ↗

  9. 📜 New paper at ICLR. On the Interaction of Compressibility and Adversarial Robustness. Read more ↗

  10. 📜 New paper at Machine Learning: Health. A Multi-Source Domain Fine-Tuning Framework for Deep Generalization in Physiological Time Series. Read more ↗

  11. 📜 New paper at npj Digital Medicine. The Cost of Explainability in AI-Enhanced ECG Models. Read more ↗

  12. 🏆 I am now a Scilifelab Group leader. Read more ↗

  13. 📜 New paper at Journal of Electrocardiology. Evaluation of AI ECG Age in the Prediction of Cardiovascular Diseases and Risk Factors. Read more ↗

  14. Group photo with faculty from the World Heart Federation Emerging Leaders programme.

    🎬 I participated as Faculty in the World Heart Federation emerging learders programme. Teaching the next emerging learders cohorts about AI.

  15. 📜 New paper at Circulation: Arrhythmia and Electrophysiology. Prediction of Atrial Fibrillation From the ECG Using Deep Learning: A Multinational Study. Read more ↗

  16. 📜 New paper at NeurIPS. Kernel Learning with Adversarial Features: Numerical Efficiency and Adaptive Regularization.

  17. 📜 New paper at CinC. Detection of Chagas Disease from the ECG: The George B. Moody PhysioNet Challenge 2025. Read more ↗

  18. 📜 New paper at AIME. Contrasting by Augmented Patient Electrocardiograms to Learn Representations for a Foundation Model. Read more ↗

  19. 📜 New paper at Scientific Reports. Exploring the Feasibility of Olfactory Brain-Computer Interfaces.

  20. Antônio Ribeiro presenting Chagas disease screening during his SBAI plenary talk.

    🎬 I gave the plenary talk at SBAI (Simpósio Brasileiro de Automação Inteligente). Photo 2 ↗

  21. 🏆 I am now a member of ELLIS (European Laboratory for Learning and Intelligent Systems). Read more ↗

  22. 📜 New paper at ICML. Human-Aligned Image Models Improve Visual Decoding from the Brain. Read more ↗

  23. 📜 New paper at ICASSP. Deep Learning Amplified Early Stopping Bias: Overestimating Performance on Small Datasets.

  24. 📜 New paper at The Lancet Digital Health. AI-Enhanced ECG for the Identification of a Sex-Related Cardiovascular Risk Continuum.

  25. 📜 New paper at AISTATS. Efficient Optimization Algorithms for Linear Adversarial Training. Read more ↗

  26. 📜 New paper at npj Digital Medicine. Evaluating AI-ECG in a longitudinal study. Read more ↗

  27. 📜 New editorial at European Heart Journal. We discuss the challenges and promisses of AI-ECG. Read more ↗

  28. ✈️ One month research visit to Francis Bach group at INRIA during Novemeber 2024.

  29. 📜 New Paper on Lancet Digital Health. We develop and validate a new AI-ECG cardiovascular risk estimator, Read more ↗

  30. 📜 New survey on the Deep learning for System identification at Automatica. Read more ↗

  31. 📜 New paper at NeurIPS (spotlight). Pre-trained transformers are aligned with Human olfactory perception. Read more ↗

  32. 📝 I am hiring! Two new fully funded PhD position and one postdoc position. Read more ↗

  33. 📜 New paper at ICML. We provide a high-dimensional analysis of PCA + Linear regression (PCR). Read more ↗

  34. 📜 Two new papers: npj Digital Medicine and Scietific Reports. AI-ECG for predicting electrolytes and cardiometabolic disease. Reference 1 ↗Reference 2 ↗

  35. 🎓 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. Read more ↗

  36. 📜 New paper about generalization of deep learning in AI-ECG. Read more ↗

  37. 👨🏻‍🏫 I started as Assistant Professor at Uppsala University Read more ↗

  38. 🎓 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. Read more ↗

  39. 🎬 Talk at Karolinska as part of DDLS fellows program. Read more ↗

  40. 📜 New paper about knowledge discovery in AI-ECG accepted in EHJ Digital Health Read more ↗

  41. ✈️ I started as postdoctoral researcher at KTH Royal Institute of Technology, Sweden, Read more ↗

  42. 🎬 I present my work in the seminar series from the National Laboratory of Scientific Computing (Brazil) Read more ↗

  43. 📜 New paper accepted at NeurIPS as a spotlight. Read more ↗

  44. 📜 New publications at Journal of Electrocardiology: Risk Prediction of Atrial Fibrillation from the 12-Lead ECG by a Deep neural network. Read more ↗

  45. 🎬 I presented my work on the European Research Network System Identification (ENRSI) workshop in Stockholm Read more ↗

  46. 📜 Two new publications: one at Circulation and one at the European Heart Journal Digital Health. Reference 1 ↗Reference 2 ↗

  47. Group photo during Antônio Ribeiro's research visit to Fu Siong's group at Imperial College London.

    ✈️ I visiting Fu Siong group at Imperial college for one week. Read more ↗

  48. 📜 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 Reference 1 ↗Reference 2 ↗

  49. 🎬 Two online talks today. One at PUC-Rio-Brazil and one at IEEE EMBS Germany Chapter in Göttingen!. Reference 1 ↗Reference 2 ↗

  50. 📜 Paper accepted at IEEE Signal Processing Letters. Invertible Kernel PCA with Random Fourier Features Read more ↗

  51. 📜 Paper accepted at Frontiers in Cardiovascular Medicine. Association of lifestyle with deep-learning based ECG-age Read more ↗

  52. 📜 Paper accepted at IEEE Transactions on Signal Processing. Overparameterized Linear Regression under Adversarial Attacks Read more ↗

  53. 📜 Paper accepted at IEEE Transactions on Biomedical Engineering. On Merging Feature Engineering and Deep Learning Read more ↗

  54. ✈️ I was awarded the ELISE Mobility Grant for a research visit to Francis Bach group at ENS/INRIA during Spring 2023.

  55. 🎬 Talk at Aalto University and ELLIS unit Helsinki! "Adversarial Attacks in Linear Regression". Read more ↗

  56. 📜 Paper accepted at Scientific Reports. Deep learning ECG-based prediction of myocardial infarction Read more ↗

  57. Antônio Ribeiro holding his Benzelius Award certificate during the award ceremony in Uppsala.

    🏆 I received the Benzelius Award! From the Royal Academy of Sciences in Uppsala

  58. 🎓 Theogene Habineza successfully defended his MSc thesis. His master thesis generated a paper accepted for publication in Journal of Electrocadiography. Reference 1 ↗Reference 2 ↗

Get in touch

Uppsala University
Box 337
751 05 Uppsala, Sweden