webinar register page

Data Science Seminar: Mathematical Data Science for solid crystalline materials
Abstract: Most real data is ambiguous in the sense that the same real object has too many (often infinitely many) data representations. For example, any periodic lattice can be represented by infinitely many different linear bases. Data Science aims to define equivalence relations on real objects to make their classifications meaningful. The most natural equivalence of solid crystalline materials is rigid motion or isometry, because periodic crystal structures are determined in a rigid form. This talk will describe recent advances in isometry classifications of finite and periodic point sets. The implemented isometry invariants completely distinguished all (hundreds of thousands) real periodic crystals in the world's largest Cambridge Structural Database. The work is joint with colleagues from the Data Science Theory and Applications group, http://kurlin.org/index.php#group

Speaker: Vitaliy Kurlin http://kurlin.org/

Nov 22, 2021 02:00 PM in London

Webinar logo
Webinar is over, you cannot register now. If you have any questions, please contact Webinar host: LSE Statistics.