Yuanyuan Tian

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Dr. Yuanyuan Tian is a Principal Scientist at Microsoft Gray Systems Lab (GSL), and an ACM Distinguished Member. Before Microsoft, she was a Principal Research Staff Member at IBM Almaden Research Center. She obtained her Ph.D. in computer science from the University of Michigan. Her research interests include HTAP, SQL-on-Hadoop, big data federation, graph analytics platforms, and large-scale systems for machine learning. She has published two books and over 40 articles in top database venues with 4500+ citations. Dr. Tian has served in the editorial board for the new encyclopedia for Big Data, as an Associate Editor for VLDB Journal and PVLDB, and chaired various tracks in top database con

graph analytics sql-on-hadoop big data graph processing machine learning big data analytics graph-centric programming cost model hybrid warehouse bloom filter query push-down join on hadoop distributed join federation lda microblogs influence analysis job hunting industry research

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Yuanyuan Tian

Big Data Analytics: From SQL to Machine Learning and Graph Analysis

Giraph++: From "Think Like a Vertex" to "Think Like a Graph"

Building A Hybrid Warehouse: Efficient Joins between Data Stored in HDFS and Enterprise Data Warehouse (EDW)

Big Graph Analytics Systems (Sigmod16 Tutorial)

Scalable Topic-Specific Influence Analysis on Microblogs