Mohammed Zaki
Location: (Troy, NY)
Personal Research Web Page: http://www.cs.rpi.edu/~zaki/
Keywords: Data Mining, Pattern Mining, Graph and Complex Network Mining, Scalable Methods, Bioinformatics, Sequence Indexing, Motif Discovery, Social Networks, Biological Networks, Web Mining, Protein Structure
Posted on: Wednesday, May 20th, 2009
Broad Research Area: AI / Machine Learning / Robotics / Vision, Databases / Information Retrieval / Data Mining, Numerical/Scientific Computing / HPC / Data-Intensive Scalable Computing, Scientific/Medical Informatics
Research Interests:
I am interested in developing novel and scalable data mining methods, with special focus on graph and complex networks. Application domains of interest include social networks, biological networks (gene and protein interactions), web graphs, and so on.
I am very interested in scaling the methods to massive datasets, such as motif discovery in graphs with millions of nodes and edges, or motif discovery in genome scale sequences. One aspect of this problem is to develop disk-based and parallel indexing methods for graphs and sequences.
Other problems of interest include mining arbitrary-shaped subspace clusters, scaling up kernel methods, integrated mining over heterogeneous data sources, and protein structure alignment, docking and prediction.
