PIPages
Labs

Joy Arulraj

Georgia Institute of Technology, GA·Computer Science·Early-career

Machine learning models can now find objects and actions in video. But running them over large video collections is slow, and using them to answer questions takes a lot of programming.

Fields

Computer Science

Engineering

Topics

video analytics

video database management systems

database systems

Grants
1 known grant, through Mar 2028

What they work on

  1. Design query optimizers tailored to offline, exploratory video analytics that use accuracy-driven optimization to reduce the cost of running complex computer vision pipelines over large video datasets.
  2. Broaden video database systems beyond object detection to support richer queries such as action localization and object re-identification across video.
  3. Develop techniques for generating synthetic video datasets to address the shortage of large datasets caused by privacy concerns.

More about the research

Answering a question such as "find every play that led to a touchdown in this football game" can be very costly. Video database management systems aim to make such questions faster and easier to ask. Applications range from urban planning to astrophysics.

Why it matters

Analyzing large video collections currently takes heavy computing and human effort. Faster, more flexible video database systems could cut the cost of video analysis for scientists and companies in fields from urban planning to astrophysics. Synthetic video datasets could also ease research limits caused by privacy concerns.

Known grants

From NIH and NSF research grants. Labs often have other funding we can't see.

CAREER: Data Management for Exploratory Video Analytics

NSF · Apr 2023 – Mar 2028

Closest labs

Andrew Pavlo

Carnegie Mellon University, PA·Computer Science

Develop automatic code transformations that speed up user-defined functions (UDFs) inside SQL queries without requiring changes to application code.

Dan Suciu

University of Washington, WA·Computer Science

Compute upper bounds on query output size that are guaranteed never to be exceeded, deriving the tightest possible bound from information theory given statistics a database already stores, such as table cardinalities, distinct-value counts, and maximum degrees.

Zeyu Ding

Binghamton University, NY·Computer Science

Build automated tools that analyze an SQL database schema and help users interactively define a customizable privacy model specifying which data elements need differential-privacy protection, and which variant.

The school

Georgia Institute of Technology: 50 labs on PI Pages, $1.5B a year on research, 572 research doctorates a year.

More about Georgia Institute of Technology

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