Lian Duan
Whereas most data mining experts search for correlation pairs, Duan focuses on correlated sets of arbitrary size. His research focuses on correlation search, community detection, and density-based clustering and outlier detection.
Before his arrival at NJIT, Duan worked as a research assistant in the University of Iowa Department of Management Science. His most recent publications include “Finding Maximal Fully-Correlated Itemsets in Large Databases,” (Proceedings of the 2009 IEEE international Conference on Data Mining) and “A Local-density Based Spatial Clustering Algorithm with Noise,” (Information Systems, Vol.32, No.7, Nov. 2007).
He is the recipient of two doctorates, one in computer science from the Chinese Academy of Sciences, China, and one in information systems with an emphasis on data mining from The University of Iowa.
Last update: January 16, 2013
Topics: data mining, correlation search, community detection, density-based clustering, outlier detection, cloud computing

