HCI.TOP

Eunice Jun

schoolUniversity of California Los Angelesbar_chart#662 Global Rank
Total Papers
12
HCI Rank
#662
Research Areas
5
Years Active
7

Personal Information

  • KeywordsHuman-Computer InteractionProgramming LanguagesApplied StatisticsData Analysis ToolsScientific Research
  • OrganizationNo specific information available
  • Education (Institution)University of Washington
  • Emailemjun@cs.washington.edu

Social Media & Links

Biography

Eunice Jun is a doctoral student in Computer Science and Engineering at the University of Washington, advised by Jeffrey Heer and Rene Just. Her research lies at the intersection of Human-Computer Interaction, Programming Languages, and Applied Statistics, aiming to help non-statistics experts conduct effective statistical analyses with ease. She developed high-level languages and interactive systems like Tea and Tisane to automate statistical test selection and build generalized linear models. These tools are widely used in academia and industry, significantly reducing error rates in analyses. Eunice has received the National Science Foundation Graduate Research Fellowship and collaborates closely with researchers from fields such as public health and psychology.

Work Experience

No specific work experience information available.

Education

  • 2018 – Present·University of Washington·PhD Degree
    • Field: Computer Science and Engineering

This biography was generated by AI from publicly available information and may contain delays or inaccuracies.

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