In the age of electronic social networks in which unprecedented amounts of data are are available, understanding and extracting information from networks has become a natural necessity. The goal of this project area is to develop estimators for the source of some information (think of it as a gossip) based on a snapshot of the network at some point in the future. Understanding the performance of source estimators in network classes can contribute to understanding how information flows through a network and how much information one can extract from them.

I worked with Professor Muriel Medard and Mr Ulric Ferner on using the Theory of Network Coding on Content Distribution Networks. Developed and implemented a mathematical model to measure and improve the accuracy, through Machine Learning techniques, of deliveries in AmazonFresh, Amazons grocery delivery service. I worked in RWTH Aachen Theoretical Computer Science Department during the summer of 2010 building efficient graph-theory algorithms to be compared with the results expected from Courcelles Theorem.