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Manasi Vartak

Manasi Vartak's picture
Affiliation: 
CSAIL MIT
Research Category: 
Systems and Tools
Primary CSAIL Advisor: 
Sam Madden
Short Bio: 

Manasi is a PhD student in the Database Group at MIT CSAIL advised by Sam Madden. Her research focuses on building interactive tools to enable rapid data analysis via visualization and machine learning. She holds Bachelors degrees in Computer Science and Mathematics from Worcester Polytechnic Institute, and a Masters degree from MIT.

Description of Research: 

Analyzing data to make decisions, to build new products or to make processes more efficient has become a top priority across industries. However, the growth in data and data analysis use cases has far outstripped the number of trained data scientists and tools for analysis. Manasi’s research involves developing new types of analytical tools to accelerate the process of going from data to actionable insights. She builds systems tailored to the real-world practice of data analysis using a combination of systems optimizations, statistical techniques, and human-in-the-loop design. Towards this goal, Manasi has worked on SeeDB, a novel type of recommendation system for visual data analysis. Given a dataset and analytical task, SeeDB searches through thousands of visualizations to automatically recommend those showing trends of interest. Manasi also works on efficient tooling to enable iterative machine learning. She is currently working on a system called Sherlock that is designed to support the entire modeling process including efficient building and testing of hundreds of models, management of workflows, and meta-analyses across models.

Publication: 

Aaron J. ElmoreJennie DugganMike StonebrakerMagdalena BalazinskaUgur ÇetintemelVijay GadepallyJ. HeerBill HoweJeremy KepnerTim KraskaSamuel MaddenDavid MaierTimothy G. MattsonS. PapadopoulosJ. ParkhurstNesime TatbulManasi VartakStan Zdonik:
A Demonstration of the BigDAWG Polystore System. PVLDB 8(12)1908-1919 (2015)

Manasi VartakSajjadur RahmanSamuel MaddenAditya G. ParameswaranNeoklis Polyzotis:
SEEDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics. PVLDB 8(13)2182-2193 (2015)

Manasi VartakSamuel MaddenAditya G. ParameswaranNeoklis Polyzotis:
SEEDB: Automatically Generating Query Visualizations. PVLDB 7(13)1581-1584 (2014)

Rebecca TaftManasi VartakNadathur Rajagopalan SatishNarayanan SundaramSamuel MaddenMichael Stonebraker:
GenBase: a complex analytics genomics benchmark. SIGMOD Conference 2014177-188

Manasi VartakSamuel Madden:
CHIC: a combination-based recommendation system. SIGMOD Conference 2013981-984