Aaron Elmore

About

Aaron Elmore is an Associate Professor of Computer Science at the University of Chicago. The page does not provide specific details about his research focus, background, or key contributions.

Research topics

• Computer Science
• Data Mining
• Artificial Intelligence
• Information Retrieval
• Database
• Mathematics
• Statistics
• Machine Learning
• Social Science
• Distributed computing

Selected publications

• Volume under the surface

  Proceedings of the VLDB Endowment · 2022 · 106 citations

  Anomaly detection (AD) is a fundamental task for time-series analytics with important implications for the downstream performance of many applications. In contrast to other domains where AD mainly focuses on point-based anomalies (i.e., outliers in standalone observations), AD for time series is also concerned with range-based anomalies (i.e., outliers spanning multiple observations). Nevertheless, it is common to use traditional point-based information retrieval measures, such as Precision, Rec…

  PublisherDOI

• How Large Language Models Will Disrupt Data Management

  Proceedings of the VLDB Endowment · 2023 · 97 citations

  Large language models (LLMs), such as GPT-4, are revolutionizing software's ability to understand, process, and synthesize language. The authors of this paper believe that this advance in technology is significant enough to prompt introspection in the data management community, similar to previous technological disruptions such as the advents of the world wide web, cloud computing, and statistical machine learning. We argue that the disruptive influence that LLMs will have on data management wil…

  PublisherDOI

• Decomposed bounded floats for fast compression and queries

  Proceedings of the VLDB Endowment · 2021 · 54 citations

  Senior authorCorresponding

  Modern data-intensive applications often generate large amounts of low precision float data with a limited range of values. Despite the prevalence of such data, there is a lack of an effective solution to ingest, store, and analyze bounded, low-precision, numeric data. To address this gap, we propose Buff, a new compression technique that uses a decomposed columnar storage and encoding methods to provide effective compression, fast ingestion, and high-speed in-situ adaptive query operators with…

  PublisherDOI

• Debunking Four Long-Standing Misconceptions of Time-Series Distance Measures

  2020 · 54 citations

  Distance measures are core building blocks in time-series analysis and the subject of active research for decades. Unfortunately, the most detailed experimental study in this area is outdated (over a decade old) and, naturally, does not reflect recent progress. Importantly, this study (i) omitted multiple distance measures, including a classic measure in the time-series literature; (ii) considered only a single time-series normalization method; and (iii) reported only raw classification error ra…

  DOI

• Good to the Last Bit: Data-Driven Encoding with CodecDB

  2021-06-09 · 43 citations

  articleSenior author

  Columnar databases rely on specialized encoding schemes to reduce storage requirements. These encodings also enable efficient in-situ data processing. Nevertheless, many existing columnar databases are encoding-oblivious. When storing the data, these systems rely on a global understanding of the dataset or the data types to derive simple rules for encoding selection. Such rule-based selection leads to unsatisfactory performance. Specifically, when performing queries, the systems always decode da…

  PublisherDOI

Recent grants

• CAREER: Intermittent Query Processing

  NSF · $580k · 2021–2026

Frequent coauthors

• Sanjay Krishnan

  University of Chicago

  38 shared

• Michael J. Franklin

  University of Chicago

  37 shared

• John Paparrizos

  The Ohio State University

  22 shared

• Zechao Shang

  Snowflake Inc. (United States)

  21 shared

• Samuel Madden

  21 shared

• Tim Mattson

  18 shared

• Michael Stonebraker

  Massachusetts Institute of Technology

  17 shared

• Aditya Parameswaran

  15 shared

Education

• Ph.D., Computer Science

  University of California, Santa Barbara

  2015

• M.S.

  University of Chicago

Awards & honors

• 2021 CAREER Award
• UChicago CS Faculty Receive Industry Grants From J.P. Morgan…
• Aaron Elmore Promoted to Associate Professor at UChicago Com…
• Six UChicago CS Faculty Receive CAREER Awards
• Intel Research Awards Go To Two UChicagoCS Faculty for Video…

Similar researchers at University of Chicago

• Ian Fosterh-150
• David Cashh-75