Tang and Zhou receive NSF Award

Jiliang Tang and Jiayu Zhou, Assistant Professors of Computer Science and Engineering at Michigan State University, have been awarded an NSF grant entitled "Unsupervised Feature Selection in the Era of Big Data".

Feature selection has been proven to be efficient and effective in preparing high-dimensional data for data mining and machine learning applications, especially when the original features are important for model interpretation and knowledge extraction. The growth of data in both size and complexity accelerates rapidly as the dramatic increase of the capacity to collect data. Such big data has imposed tremendous challenges on traditional feature selection methods, which are usually designed to handle homogeneous and static data in a centralized fashion. Meanwhile in many real-world domains big data is unlabeled, which further exacerbates the difficulty. Therefore, the majority of existing feature selection methods are not well prepared for big data, and this thus calls for the development of novel unsupervised feature selection for unlabeled big data. The project extends the state-of-the-art feature selection research to a new frontier of taming big data. It has potential to benefit a number of real-world applications from various disciplines such as Computer Science, Business, Education, Politics, Healthcare and Bioinformatics.

(Date Posted: 2017-08-14)