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  • CS Colloquium: Leilani Battile (CSAIL MIT) - Behavior-Driven Optimizations for Big Data Exploration

    Mon, Feb 06, 2017 @ 11:00 AM - 12:20 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars

    Speaker: Leilani Battile , CSAIL MIT

    Talk Title: Behavior-Driven Optimizations for Big Data Exploration

    Series: CS Colloquium

    Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.

    The physical and biological sciences are becoming more data driven, often due overwhelming quantities of data collected from satellites, telescopes, sequencers, and other sensors. One of the key issues for scientists who work with large datasets is efficient visualization of their data to extract patterns, observe anomalies, and debug their workflows. Though a variety of visualization tools exist to help people make sense of their data, these tools often rely on database management systems (or DBMSs) for data processing and storage; and unfortunately, DBMSs fail to process the data fast enough to support a fluid, interactive visualization experience.

    My work blends optimization techniques from databases and methodology from HCI and visualzation in order to support interactive and iterative exploration of large datasets. In this talk, I will discuss Sculpin, a visual exploration system that learns user exploration patterns automatically, and exploits these patterns to pre-fetch data ahead of users as they explore. I will show that Sculpin's pre-fetching techniques provide significant performance benefits compared to existing systems. I will then discuss our ongoing work with Sculpin, which aims to avoid wasting computational resources, while still providing a fluid, interactive exploration experience for users. To do this, we combine data-prefetching with incremental data processing and visualization-focused caching optimizations, and incorporate these techniques in Sculpin to further boost performance.

    Biography: Leilani Battile is a Computer Science Ph.D. candidate in the CSAIL Database Group at MIT, advised by Prof. Michael Stonebraker. Her research interests lie at the intersection of data management, user interface design, and visual analytics, with the aim of building intuitive and scalable database exploration tools. She was a National Science Foundation Graduate Fellow from 2011 to 2013. She obtained a M.S. from MIT in 2013, and a B.S. in Computer Engineering from the University of Washington in 2011.

    Host: CS Department

    Location: Ronald Tutor Hall of Engineering (RTH) - 217

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

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