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Kamensky's work addresses a central challenge of computational mechanics, namely, the difficulty of translating realistic, geometrically-complex problems into computational models.  His research aims to streamline—or even automate—computational mechanics, by developing more geometrically-flexible analysis methods.

Capsule Bio:

Kamensky was a postdoctoral researcher at Brown University and earned his Ph.D. at the University of Texas, Austin, before joining Â鶹´«Ã½ in 2019.