The Bloomberg Data Science Research Grant Program aims to support cutting-edge research in the broad field of machine learning, including specific areas such as natural language processing, information retrieval, machine-translation and deep neural networks. In April 2015 they announced their first round of recipients and in October 2015 they announced their second.
Out of hundreds of applications from faculty members at universities around the world, a committee of Bloomberg researchers selected the proposals of eight research projects. One of the research proposal projects selected is APPM's Stephen Becker's Online clustering of time-sensitive data.
Stephen Becker (University of Colorado at Boulder):
Online clustering of time-sensitive data: Modern datasets, such as news articles or tweets, have a time-sensitive nature which is not well captured by traditional offline supervised or unsupervised learning. Prof. Becker’s work will extend some clustering algorithms to work with streaming data and adapt modern variance-reduction strategies to an online setting.