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Mohammed J. Zaki is a Professor of Computer Science at RPI. He received his Ph.D. degree in computer science from the University of Rochester in 1998. His research interests focus on developing novel data mining techniques, especially in bioinformatics. He has published over 200 papers and book-chapters on data mining and bioinformatics. He is the founding co-chair for the BIOKDD series of workshops. He is currently Area Editor for Statistical Analysis and Data Mining, and an Associate Editor for Data Mining and Knowledge Discovery, ACM Transactions on Knowledge Discovery from Data, Knowledge and Information Systems, ACM Transactions on Intelligent Systems and Technology, Social Networks and Mining, and International Journal of Knowledge Discovery in Bioinformatics. He was/is the program co-chair for SDM'08, SIGKDD'09, PAKDD'10, BIBM'11, CIKM'12, and ICDM'12. He received the National Science Foundation CAREER Award in 2001 and the Department of Energy Early Career Principal Investigator Award in 2002. He received the HP Innovation Research Award in 2010, 2011, and 2012, and the Google Faculty Research Award in 2011. He is a senior member of the IEEE, and an ACM Distinguished Scientist. His research is supported in part by NSF, NIH, DOE, Google, HP, and Nvidia.

• Data Mining Template Library (Itemsets, Sequences, Trees, and Graphs)
• Itemset Mining and Association Rules (Eclat, Charm, Charm-L, GenMax, BLOSOM
• Sequence Mining (Spade, cSpade)
• Tree Mining and XML Classification (TreeMiner, TreeMiner-D, PatternMatcher, SLEUTH, XRules)
• Graph Mining and Sampling (Origami, MUSK)
• Shape-based Categorical and Microarray Clustering (CLICKS, Sparcl, ROBIN, TriCluster, MicroCluster)
• Biological Sequence Analysis: HMM, Suffix Trees, Structured Motifs (VOGUE HMM, Trellis, Trellis+, sMotif, ExMotif)
• Protein Structure Alignment, Protein Folding, Protein Docking, Protein Indexing (SNAP, FlexSNAP, UNFOLD, ContextShapes, PSIST)
• Real and Synthetic Datasets (IBM Generator, Dense Itemset Datasets, Tree Generator, CSLOGS, Xrules LOGML, PlanData)

• ACM SIGKDD International Workshops on Data Mining in Bioinformatics (BIOKDD)
• ICDM Workshops on Frequent Itemset Mining Implementations (FIMI)
• ACM SIGKDD Workshop on Large Scale Parallel KDD Systems
• ACM SIGKDD Workshop on Open Source Data Mining
• International Workshops on High Performance Data Mining (HPDM)
• ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery (DMKD)