Metadata
Title
Leilani Battle
Category
general
UUID
fb679b91ed2145569a8ddbc39e9b8100
Source URL
https://homes.cs.washington.edu/~leibatt/experience.html
Parent URL
https://homes.cs.washington.edu/~leibatt/bio.html
Crawl Time
2026-03-11T03:31:31+00:00
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Leilani Battle

Source: https://homes.cs.washington.edu/~leibatt/experience.html Parent: https://homes.cs.washington.edu/~leibatt/bio.html

Education

Massachusetts Institute of Technology, Cambridge, MA (Spring 2017)

PhD Candidate, Computer Science, GPA 5.0/5.0

Thesis: “Behavior-Driven Optimization Techniques for Scalable Data Exploration”

Advisor: Michael Stonebraker

Massachusetts Institute of Technology, Cambridge, MA (August 2013)

MS, Computer Science, GPA 5.0/5.0

Thesis: “Interactive Visualization of Big Data Leveraging Databases for Scalable Computation”

Advisor: Michael Stonebraker

University of Washington, Seattle, WA, (June 2011)

BS, Computer Engineering, GPA 3.77/4.0

Appointments

University of Washington, Seattle, WA (Jul 2021-Present)

Assistant Professor, Paul G. Allen School of Computer Science and Engineering

I co-lead the Interactive Data Lab with Prof. Jeffrey Heer.

University of Maryland, College Park, MD (Aug 2018-Jun 2021)

Assistant Professor, Computer Science Department

I led the Battle Data (BAD) Lab, which focuses on developing intuitive and interactive tools to support big data science.

University of Washington, Seattle, WA (July 2017-July 2018)

Postdoc, Paul G. Allen School of Computer Science and Engineering

I worked with Jeffrey Heer in the Interactive Data Lab on characterizing user visual analysis behavior with standard visualization tools (e.g., Tableau), to: 1) inform the design of new visualization recommendation systems; and 2) to develop realistic workloads (and ultimately benchmarks) for testing the performance scalable visual analytics tools.

Microsoft Research, Redmond, WA (Summer 2014)

Research Intern

I worked with Danyel Fisher in the VIBE group, focusing on HCI and visualization. I developed new techniques for recording query provenance in data stream management systems. I used the resulting provenance data to design a more intuitive user interface for visually debugging temporal database queries. Our work was presented at CHI, a premier conference for human-computer interaction research.

Telenav R&D, (Summer 2012)

Technical Intern

I developed a tool for recommending relevant destinations to users planning a new trip via a GPS device or smartphone.

Grants and Awards

Sloan Research Fellow

Year: 2023, Amount: $75,000 - IEEE Technical Committee on Data Engineering

TCDE Rising Star Award

Year: 2022 - National Science Foundation (NSF)

Computer and Information Science and Engineering (CISE)

CAREER Award

Year: 2022, Amount: $570,541 - VMWare

Early Career Faculty Grant

Year: 2021, Amount: $50,000 - MIT Technology Review

MIT TR 35 Under 35 Award

Year: 2020 - Adobe

Data Science Research Award

Year: 2019, Amount: $58,000 - Oak Ridge Associated Universities (ORAU)

Ralph E. Powe Junior Faculty Enhancement Award

Year: 2019, Amount: $10,000 - National Science Foundation (NSF)

Computer and Information Science and Engineering (CISE)

Research Initiation Initiative (CRII) Award

Year: 2019, Amount: $175,000 - Schloss Dagstuhl/National Science Foundation (NSF)

Travel Grant for Junior Researchers

Years: 2017 and 2018 - University of Washington

Office of Postdoctoral Affairs

Postdoc Travel Award

Year: 2018 - ACM SIGMOD

Student Travel Grant

Year: 2015 - National Science Foundation (NSF)

Graduate Research Fellowship Program (GRFP) Award

Year: 2013

Leadership and Service

Co-Chair/Co-Organizer

PC Member

External Reviewer: Journals

External Reviewer: Conferences

University/Department Service

Teaching

Courses Taught

Advised and Co-Advised PhD Students