Presented By O'Reilly and Cloudera
Make Data Work
22–23 May 2017: Training
23–25 May 2017: Tutorials & Conference
London, UK
Dr. Vijay Srinivas Agneeswaran

Dr. Vijay Srinivas Agneeswaran
Director of Technology, SapientNitro

Website | @a_vijaysrinivas

Vijay Srinivas Agneeswaran is director of technology at SapientNitro. Vijay has spent the last 10 years creating intellectual property and building products in the big data area at Oracle, Cognizant, and Impetus, including building PMML support into Spark/Storm and implementing several machine-learning algorithms, such as LDA and random forests, over Spark. He also led a team that build a big data governance product for role-based, fine-grained access control inside of Hadoop YARN and built the first distributed deep learning framework on Spark. Earlier in his career, Vijay was a postdoctoral research fellow at the LSIR Labs within the Swiss Federal Institute of Technology, Lausanne (EPFL). He is a senior member of the IEEE and a professional member of the ACM. He holds four full US patents and has published in leading journals and conferences, including IEEE Transactions. His research interests include distributed systems, cloud, grid, peer-to-peer computing, machine learning for big data, and other emerging technologies. Vijay holds a a bachelor’s degree in computer science and engineering from SVCE, Madras University, an MS (by research) from IIT Madras, and a PhD from IIT Madras.


16:3517:15 Thursday, 25 May 2017
Level: Beginner
The class of big data computations known as distributed merge trees was built to aggregate user information across multiple data sources in the media domain. Vijay Srinivas Agneeswaran explores prototypes built on top of Apache HAWQ, Druid, and Kinetica, one of the open source GPU databases. Results show that Kinetica on a single G2.8x node outperformed clusters of HAWQ and Druid nodes. Read more.