The nominating institution Leibniz Universität Hannover on the breakthrough:

Current patient-specific simulation workflows based on CT or MRI rely on the intervention of specially trained analysts. The associated cost and response times, however, are incompatible with tight budgets and urgent decision-making in clinical practice. This project re-thinks accurate physiology-based computational modeling based on diagnostic imaging data. The resulting fully automated tools enable the close integration of patient-specific predictive simulation in clinical decision-making.

Tags: Digital Health, Digitalisation, Engineering, Med-Tech, Mobile Health.

Dominik Schillinger

Leibniz University Hannover

Dominik Schillinger completed his doctoral degree at TUM in 2012. After postdoctoral training at UT Austin and serving on the faculty of the University of Minnesota, he moved to the Leibniz University Hannover in 2019. During his career, his work at the interface between mechanics, applied mathematics and scientific computing has received numerous awards, including the IACM John Argyris Award, the GAMM Richard von Mises Prize, the ICE Zienkiewicz Medal, the NSF CAREER Award, a DFG Emmy Noether grant, an ERC Starting Grant, the EMI Leonardo da Vinci Award, and the PECASE from the White House.

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