IEEE TNSE Best Paper Award 2019

Monday, April 8, 2019 - 10:30

IEEE TNSE Best Paper Award 2019

A paper coauthored by the director of the Hamilton Institute, Ken Duffy, with collaborators Soheil Feizi, Ali Makhdoumi, Manolis Kellis, and Muriel Médard from MIT has won the IEEE Transactions on Network Science and Engineering Best Paper Award 2019. The award is for the best paper of all those published between 2016 and 2018.

The article, "Network Maximal Correlation", introduces a new statistic for measuring dependency in multivariate random variables, as well as introducing a computational framework to evaluate it given multivariate data sets. The goal of the new measure is to automatically identify complex, non-linear dependencies that would not be observed with traditional measures of correlation.

The IEEE announcement can be found at