I am a Senior Research SDE in the Data Management, Exploration and Mining (DMX) group in Microsoft Research. I received my Ph.D. degree in Computer Science from Duke University in May 2012. My dissertation work titled "Automatic Tuning of Data-Intensive Analytical Workloads" presents a novel dynamic optimization approach that can form the basis for tuning workload performance automatically across different tuning scenarios and systems.
My research interests are in large-scale Data Processing Systems and Database Systems. In particular, my work focuses on ease-of-use, manageability, and automated tuning of both centralized and distributed data-intensive computing systems. In addition, I am interested in applying database techniques in other areas like scientific computing, bioinformatics, and numerical analysis. For more information regarding my past work, please visit my Duke homepage.
- Shivnath Babu and Herodotos Herodotou, Massively Parallel Databases and MapReduce Systems, in Foundations and Trends® in Databases, NOW Publishers, 20 November 2013
- Herodotos Herodotou and Shivnath Babu, A What-if Engine for Cost-based MapReduce Optimization, in Bulletin of the IEEE Computer Society Technical Committee on Data Engineering, March 2013
- Harold Lim, Herodotos Herodotou, and Shivnath Babu, Stubby: A Transformation-based Optimizer for MapReduce Workflows, in Proc. of the VLDB Endowment (PVLDB), vol. 5, no. 11, pp. 1196--1207, VLDB Endowment, August 2012
- Herodotos Herodotou, Fei Dong, and Shivnath Babu, No One (Cluster) Size Fits All: Automatic Cluster Sizing for Data-intensive Analytics, in Proceedings of the 2nd ACM Symposium on Cloud Computing (SOCC), ACM, October 2011
- Faheem Mitha, Herodotos Herodotou, Nedyalko Borisov, Chen Jiang, Josh Yoder, and Kouros Owzar, SNPpy - Database Management for SNP Data from GWAS Studies, in PLoS ONE, vol. 6, no. 10, Public Library of Science, October 2011
- Herodotos Herodotou and Shivnath Babu, Profiling, What-if Analysis, and Cost-based Optimization of MapReduce Programs, in Proc. of the VLDB Endowment (PVLDB), vol. 4, no. 11, pp. 1111–1122, VLDB Endowment, August 2011
- Herodotos Herodotou, Nedyalko Borisov, and Shivnath Babu, Query Optimization Techniques for Partitioned Tables, in Proceedings of the 2011 ACM International Conference on Management of Data (SIGMOD), ACM, June 2011
- Herodotos Herodotou, Harold Lim, Gang Luo, Nedyalko Borisov, Liang Dong, Fatma Bilgen Cetin, and Shivnath Babu, Starfish: A Self-tuning System for Big Data Analytics, in Proceedings of the Fifth Biennial Conference on Innovative Data Systems Research (CIDR), January 2011
- Herodotos Herodotou and Shivnath Babu, Xplus: A SQL-Tuning-Aware Query Optimizer, in Proc. of the VLDB Endowment (PVLDB), vol. 3, no. 1-2, pp. 1149–1160, VLDB Endowment, September 2010
- Herodotos Herodotou and Shivnath Babu, Automated SQL Tuning through Trial and (Sometimes) Error, in Proceedings of the Second International Workshop on Testing Database Systems (DBTest), June 2009
- Shivnath Babu, Nedyalko Borisov, Songyun Duan, Herodotos Herodotou, and Vamsidhar Thummala, Automated Experiment Driven Management of (Database) Systems, in Proceedings of the 12th Workshop on Hot Topics in Operating Systems (HotOS-XII), May 2009
- Yi Zhang, Herodotos Herodotou, and Jun Yang, RIOT: I/O-Efficient Numerical Computing without SQL, in Proceedings of the Fourth Biennial Conference on Innovative Data Systems Research (CIDR), January 2009
Contact InfoMicrosoft Corporation
One Microsoft Way
Redmond, WA 98052-6399
Email: herohero at microsoft dot com
|Research Demos During PDC10 Inspire|
|From Quantum Computing to Show Dogs, Faculty Summit Informed and Inspired
|Moving Food-Resilience Data to the Cloud
|How Might Climate Change Affect Our Food Supply?