Sascha Ranftl

Sascha Ranftl is an Erwin Schrödinger Fellow at the Courant Institute of Mathematical Sciences, New York University. Their research spans interdisciplinary domains including Bayesian probability theory, uncertainty quantification, computational engineering, and biomedical applications.

• Affiliation: Courant Institute, NYU
• Former Affiliation: Graz University of Technology (Institute of Theoretical Physics & Computational Physics, Graz Center of Computational Engineering)

Research Interests: Ranftl's work focuses on integrating Bayesian inference with machine learning and physics-informed modeling to address uncertainty quantification in biomedical simulations, particularly for aortic dissection and impedance cardiography. Their approach harmonizes statistical rigor with engineering pragmatism, emphasizing surrogate models and computational fluid dynamics.

Recent Publications: Analyze geometric uncertainties in patient-specific blood vessels, develop physics-consistent neural networks, and apply Bayesian frameworks to biomedical diagnostics and elastoplastic material modeling.

Scientific Awards:

• Erwin Schrödinger Fellowship

Contact:

• ranftl@tugraz.at
• sranf@duck.com