Assistant Professor of Mathematics Gabor Lippner has been awarded a three year National Science Foundation grant for his research in network science.
Lippner seeks to understand what makes networks tick, combining many different tools from geometry and advanced analysis. One of the challenges he faces in his work is briding the gap between continuous and discrete mathematics. Continuous math deals with real numbers, whereas discrete mathematics deals with sets of items. Gabor explains that networks are discrete objects, and therefore tools must be adapted to work in this space.
This new grant hopes to expand what we know about networks. In particular, Lippner says the grant “aims to improve our understanding of what it means for two large netwokrs to be similar to each other.” Previous work has determined various definitions of similarity for networks, but Lippner believes that it’s yet unclear “whether there is a ‘best’ notion one should stick to.”
Building better base understanding of networks is a great way to improve tools for analysis of networks. As data has gotten larger in the modern world, many of our best tools to analyze data have proven too slow or useless against big data and networks. Researchers like Lippner seek out new tools and approaches to analyzing networks in a world where networks and big data are becoming more and more prevalent.
The grant from the National Science Foundation will help support graduate students in Lippner’s lab as well as fund travel to conferences.