Siemens Inventor of the Year Award 2020, Category Talents

It is with a great honor that I received the very prestigious Siemens Inventor of the Year 2020 award along with other Siemens fellows. I am so humbled to be part of Siemens Inventors family, who made so many contributions to the society. This would not have been possible without all the colleagues, mentors and collaborators with whom I had the chance to work with, with whom we strived to realize our vision of a digital twin of the heart, such a potentially disruptive technology. I am so grateful to all of them, this award is for them! Thank you everyone, let us keep pushing the limits of the technology and make digital twins a healthcare reality!

Best Presentation Award at MICCAI – STACOM 2020

Heartfelt congratulations to Felix Meister and team for winning the best oral presentation award at the STACOM 2020 workshop, a satellite event of MICCAI 2020. The award was given for his work on “Graph convolutional regression of cardiac depolarization from sparse endocardial maps”.

In this paper, we show how geometric deep learning can be used to extrapolate electrophysiology signals throughout the myocardium given sparse and noisy endocardial measurements. A big thank you to our collaborators from JHU (Baltimore, MD), Dr. Ashikaga and Dr. Halperin, as well as the Pattern Recognition Lab at FAU (Erlangen, Germany). Congratulations to the entire team!

The paper can be accessed here:

Check out our new book on “AI for Computational Modeling of the Heart”

Our new book presents recent research developments towards streamlined and automatic estimation of the digital twin of a patient’s heart by combining computational modeling of heart physiology and artificial intelligence. The book first introduces the major aspects of multi-scale modeling of the heart, along with the compromises needed to achieve subject-specific simulations. Reader will then learn how AI technologies can unlock robust estimations of cardiac anatomy, obtain meta-models for real-time biophysical computations, and estimate model parameters from routine clinical data. Concepts are all illustrated through concrete clinical applications.

The content of the book is the result of many years of research and hard work from the team, pushing the limit of personalized computational modeling of the heart. So proud of the team! Congratulations to everyone for this achievement! I hope you will enjoy reading the as much as we enjoyed writing it!