A recent trend, emerging independently in multiple theoretical and
applied communities, is to understand collections or networks of
geometric data sets through their relations and interconnections, a
point of view that can be broadly described as exploiting the
functoriality of data, which has a long tradition associated with it in
mathematics. Functoriality, in its broadest form, is the notion that in
dealing with any kind of mathematical object, it is at least as important
to understand the maps, transformations or symmetries possessed by
the object or the family of objects to which it belongs, as it is to study
the object itself. This general idea has led to deep insights into the
structure of various geometric spaces as well as to the state-of-the-art
methods in various application domains.
Chaired by Prof Leonidas J. Guibas, IAS Senior Visiting Fellow from
Stanford University; and coordinated by Prof Siu-Wing Cheng, Professor
of Computer Science and Engineering at HKUST and professors from
France and Israel, a 5-day focused program on Functoriality in
Geometric Data was held on 13-17 April 2015 at IAS. This focused
program brought together 5 plenary speakers, 15 invited speakers and
over 33 participants from Hong Kong and overseas to explore and
exploit functoriality in geometric data from an algorithmic perspective.
IAS Focused Program on
Functoriality in
Geometric Data
May 2015
Event Highlights
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