Aviv A. Rosenberg

PhD Student @ CS, Technion • MLE & Data Scientist @ Sibylla

I’m a PhD student in the VISTA Lab at the Technion Computer Science Faculty, advised by Prof. Alex Bronstein. In addition, I’m currently working as a machine learning engineer and data scientist at Sibylla.

My research interests include deep learning, differentiable optimization, physiological signal processing (e.g. ECG), and recently computational structural biology. I hold an MSc in Biomedical Engineering and a BSc in Electrical Engineering, both from the Technion. Currently head TA of the CS faculty’s Deep Learning course.

In addition to a my research pursuits, I have a strong technical background in software development. Before starting my PhD I worked in multiple technical roles. I have extensive experience writing robust, testable, well-designed code, leading software teams and architecting large-scale systems.


Jul 23, 2021 Our Deep Learning in Cardiology paper featured by Technion.
Jun 14, 2021 New paper in PNAS about deep learning in cardiology.
Aug 24, 2020 CHE Data Science Scholarship awarded.
Jul 19, 2020 Our new paper was published in Nature Scientific Reports.

selected publications

  1. Frontiers
    PhysioZoo: a novel open access platform for heart rate variability analysis of mammalian electrocardiographic data
    Behar, Joachim A, Rosenberg, Aviv A, Weiser-Bitoun, Ido, Shemla, Ori, Alexandrovich, Alexandra, Konyukhov, Eugene, and Yaniv, Yael
    Frontiers in Physiology 2018
  2. Nat. Sci. Rep.
    Signatures of the autonomic nervous system and the heart’s pacemaker cells in canine electrocardiograms and their applications to humans
    Rosenberg, Aviv A, Weiser-Bitoun, Ido, Billman, George E, and Yaniv, Yael
    Nature Scientific Reports 2020
  3. PNAS
    Meeting the unmet needs of clinicians from AI systems showcased for cardiology with deep-learning–based ECG analysis
    Elul, Yonatan, Rosenberg, Aviv A., Schuster, Assaf, Bronstein, Alex M., and Yaniv, Yael
    Proceedings of the National Academy of Sciences 2021