
About
David Tewodrose is a Professor in the Department of Mathematics and Data Science at the Vrije Universiteit Brussel (Belgium). His research focuses on geometric analysis, particularly studying metric measure spaces obtained as Gromov-Hausdorff limits of Riemannian manifolds under curvature constraints. He leads the Odysseus Programme titled Geometric and Analytic Properties of Metric Measure Spaces with Spectral Curvature Constraints, with Applications to Manifold Learning, funded by FWO (2023–2028). This program explores geometric evolution problems, spectral optimization, and manifold learning algorithms.
He teaches differential geometry and measure theory in the VUB Bachelor program, and Riemannian geometry in the VUB-UAntwerpen Master program. Previously, he instructed analysis courses in the International Bachelor Ygrec program and supervised student blog projects on societal data science issues.
His research team includes PhD candidates Nicolo' Cont and Manuel Dias, along with postdoctoral researcher Susovan Pal. His work bridges geometric analysis with applications in data science, emphasizing curvature constraints and spectral properties.
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