Abstract:
Relational datasets are often modeled with graphs and
hypergraphs: objects become vertices and relations become edges or
hyperedges. Algorithms for graph and hypergraph visualization aim to
present such data in an effective and aesthetically appealing way.
From a theoretical point of view, the underlying problems give rise to
classical algorithmic and complexity questions. From a practical point
of view, building functional and usable visualization systems is
associated with questions about scalability and usability. We will
discuss our general visualization framework of utilizing familiar data
representation metaphors, such as geographic maps and metro maps.

Speaker Biography:
Stephen Kobourov completed BS degrees in Mathematics and Computer
Science at Dartmouth College in 1995, and a PhD in Computer Science at
Johns Hopkins University in 2000. He worked at the University of
Arizona as Assistant, Associate and Full Professor from 2000 to 2024.
Since June 2024 he is the Chair for Efficient Algorithms and TUM
Campus Heilbronn.