Representing and Analyzing Pathway Data Through Networks

The broad aim of my dissertation research is to address representation of network data in two ways. First, I address incomplete network data. Incomplete data is a problem when studying most real-world systems because data is either collected with imperfect sensors or by sampling from the system. I investigate strategies to extend samples of incomplete network data through node querying to get a more accurate representation of the system and thus improve any analysis done on the data. Second, I study the representation of sequences of interactions, also understood as pathways through a network. Network Scientists often aggregate such sequential data into a traditional weighted network representation, but this can destroy information about the system by ignoring correlations in how a network is traversed. I work with representations that encode pathway correlations and develop methodology for their analysis. My research can be applied broadly, from the study of web navigation and information seeking, to human movements through transportation systems, to understanding the global network of container shipping.

More info
February 25, 2020
9:30 am
9:30 am
Network Science Institute
177 Huntington Ave 11th floor