Aaron Huber

PhD student

Aaron has enjoyed working the past few year as a research assistant under the direction of Dr. Oliver Kennedy, Dr. Atri Rudra, Dr. Zhuoyue Zhao, and Dr. Boris Glavic. His primary interests include Probabilistic (PDB) and Incomplete Databases (from theoretical and system perspectives), computing (exact and approximate) uncertainty values, and computing/propagating measurement data through query pipelines. His most recent work includes FastPDB, a system that leverages the well known wanderjoin algorithm to avoid materialization of lineage and produce approximation results in time linear of the equivalent determinstic query. Amongst other results, the work shows (to the best of our knowledge) a link between Approximate Query Processing and PDB query processing, not previously known.

Projects

Publications

FastPDB: Towards Bag-Probabilistic Queries at Interactive Speeds
Aaron Huber, Oliver Kennedy, Atri Rudra, Zhuoyue Zhao, Su Feng, Boris Glavic
Computing expected multiplicities for bag-TIDBs with bounded multiplicities
Su Feng, Boris Glavic, Aaron Huber, Oliver Kennedy, Atri Rudra
Efficient Uncertainty Tracking for Complex Queries with Attribute-level Bounds
Su Feng, Boris Glavic, Aaron Huber, Oliver Kennedy
Uncertainty Annotated Databases - A Lightweight Approach for Approximating Certain Answers
Su Feng, Aaron Huber, Boris Glavic, Oliver Kennedy
Uncertainty Annotated Databases - A Lightweight Approach for Dealing with Uncertainty
Su Feng, Aaron Huber, Boris Glavic, Oliver Kennedy

This page last updated 2025-03-04 15:41:55 -0500