Will Epperson

I am a Ph.D. student in Human-Computer Interaction at Carnegie Mellon University, where I design and develop systems for Visual Data Debugging. Data is the foundation of recent AI advancements and data-driven decision-making, yet while we have powerful tools to debug code, data debugging remains underdeveloped. My research addresses this gap by creating systems that provide rapid, interactive overviews of datasets and streamline data exploration during programming. My work has been published at top-tier venues such as CHI and IEEE VIS, and my open-source tools are used by data scientists to support their workflows.

Education

August 2020 - Present Ph.D. in Human Computer Interaction
Carnegie Mellon University
Advisors: Dominik Moritz, Adam Perer
Sample Coursework: HCI Process and Theory, Computational Medicine, Human Judgement and Decision Making, Causality and ML, Advanced NLP

August 2020 - May 2023 M.S. in Human Computer Interaction
Carnegie Mellon University
Advisors: Dominik Moritz, Adam Perer

August 2016 — May 2020 B.S. in Computer Science
Georgia Institute of Technology
GPA: 4.0, Summa Cum Laude, threads in Intelligence and Modeling/Simulation Sample Coursework: Machine Learning, Deep Learning, Computer Vision, Computer Architecture, Algorithms, Computer Simulation, Information Visualization

Research Experience

August 2020 - PresentCarnegie Mellon University, Pittsburgh, PA
Graduate Researcher, Data Interaction Group (DIG)
Advisor: Dominik Moritz, Adam Perer
Member of the DIG research group, working on novel data visualizations, ML interpretation techniques, and interactive data systems.

January 2019 - May 2020Georgia Institute of Technology, Atlanta, GA
Undergraduate Researcher, Polo Club of Data Science
Advisor: Duen Horng (Polo) Chau
Member of the Polo Club of Data Science working on novel data visualizations to find fairness issues in Machine Learning models

January 2018 - May 2019Georgia Institute of Technology, Atlanta, GA
Undergraduate Researcher, Automated Algorithm Design
Advisor: Jason Zutty, Greg Rohling
Worked on EMADE algorithm design engine to implement sentiment analysis pipeline to analyze news articles to aid in predicting stock price movements using genetic algorithms. Led project to visualize the genetic algorithm evolution process.

Industry Experience

Summer 2024Microsoft Research, Redmond, WA
Research Intern, AI Frontiers - HAX Group
Mentor: Gagan Bansal, Victor Dibia
Research intern working on developer tools for multi-agent AI systems.

Summer 2022Databricks, San Francisco, CA
Software Engineering Contractor
Mentor: Kanit Wongsuphasawat
Designed and delivered production feature for creating dashboards by specifying fields of interest in a dataset.

Summer 2021Microsoft Research, Redmond, WA
Research Intern, VIDA Group
Mentor: Steve Drucker, Rob DeLine
Research intern working on data science tools. Lead project around reuse and sharing in data science, published at ICSE 2022. Co-author on project around visualizing data frame differences published at CHI 2022.

Summer 2019Point72 Asset Management, New York, NY
Data Analytics Intern, Market Intelligence Group
Mentor: Trevor Rempel
Worked as Data Scientist in alternative data space to clean, model, and understand large datasets

Summer 2018Ultimate Software, Weston, FL
Software Development Intern, Innovation Strategies Team
Mentor: Joseph Cutrono
Designed and developed Slack app to integrate with the UltiPro HR management tool. App published to Slack app store.

Summer 2015The Home Depot, Atlanta, GA
Software Development Intern
Developed web app for tracking candidate progress throughout hiring process for internal HR use.

Publications

Guided Statistical Workflows with Interactive Explanations and Assumption Checking
Yuqi Zhang, Adam Perer, Will Epperson
GuidedStats is a Jupyter extension that helps data scientists perform statistical analyses with guided workflows.
VIS 24: IEEE Conference on Data Visualization (VIS). St Pete Beach, Florida, 2024.
Project PDF Code

Dead or Alive: Continuous Data Profiling for Interactive Data Science
Will Epperson, Vaishnavi Gorantla, Dominik Moritz, Adam Perer
AutoProfiler is a Jupyter extension that helps data scientists understand their data and find issues during analysis through continuous data profiling.
VIS 23: IEEE Conference on Data Visualization (VIS). Melbourne, Australia, 2023.
Project PDF Code Best Paper Honorable Mention

A Declarative Specification for Authoring Metrics Dashboards
Will Epperson, Kanit Wongsuphasawat, Allison Whilden, Fan Du, Justin Talbot
Quick dashboarding presents a novel specification for dashboard authoring, comprised of sections of metrics combined with dimensions.
VDS at VIS 23: Visual Data Science Symposium (VDS). Melbourne, Australia, 2023.
Project PDF Best Paper

Leveraging Analysis History for Improved In Situ Visualization Recommendation
Will Epperson, Doris Jung-Lin Lee, Leijie Wang, Kunal Agarwal, Aditya Parameswaran, Dominik Moritz, Adam Perer
Solas is a visualization recommendation tool that uses the history of analysis for in situ recommendations in Jupyter.
EuroVis 22: Eurographics Conference on Visualization (EuroVis). Rome, Italy, 2022.
Project PDF Code BibTeX

			@article{Epperson22Solas,
  title={Leveraging Analysis History for Improved In Situ Visualization Recommendation},
  author={Epperson, Will and Lee, Doris Jung-Lin and Wang, Leijie and Agarwal, Kunal and Parameswaran, Aditya and Moritz, Dominik and Perer, Adam},
  journal={EuroVis 22: Eurographics Conference on Visualization},
  year={2022},
  publisher={EG}
  url={}
}
		

Strategies for Reuse and Sharing among Data Scientists in Software Teams
Will Epperson, April Yi Wang, Robert DeLine, Steven M. Drucker
Interviews and a survey with 149 data scientists at Microsoft revealed five distinct strategies for sharing and reusing analysis code along with factors that encourage or discourage reuse.
ICSE 22: ACM International Conference on Software Engineering (ICSE). Pittsburgh, PA, 2022.
Project PDF Recording Slides BibTeX

			@article{wang2022DITL,
  title={Strategies for Reuse and Sharing among Data Scientists in Software Teams},
  author={Epperson, Will and Wang, April Yi and DeLine, Robert and Drucker, Steven M.},
  journal={ICSE 22: ACM International Conference on Software Engineering},
  year={2022},
  publisher={ACM}
  url={}
}
		

Diff in the Loop: Supporting Data Comparison in Exploratory Data Analysis
April Yi Wang, Will Epperson, Robert DeLine, Steven M. Drucker
Diff in the Loop supports tracking, comparing, and visualizing differences in datasets during iterative data analysis.
SIGCHI 22: ACM Symposium on Computer Human Interaction (CHI). New Orleans, LA, 2022.
Project PDF BibTeX

			@article{wang2022DITL,
  title={Diff in the Loop: Supporting Data Comparison in Exploratory Data Analysis},
  author={Wang, April Yi and Epperson, Will, and DeLine, Robert and Drucker, Steven M.},
  journal={SIGCHI 22: ACM Symposium on Computer Human Interaction},
  year={2022},
  publisher={ACM}
  url={}
}
		

RECAST: Interactive Auditing of Automatic Toxicity Detection Models
Austin P. Wright, Omar Shaikh, Haekyu Park, Will Epperson, Muhammed Ahmed, Stephane Pinel, Diyi Yang, Duen Horng (Polo) Chau
Interactive Auditing of Automatic Toxicity Detection Models
24th ACM Conference on Computer-Supported Cooperative Work & Social Computing. 2021.
Project PDF BibTeX

			@article{wright2020recast,
title={RECAST: Interactive Auditing of Automatic Toxicity Detection Models},
author={Austin P. Wright and Omar Shaikh and Haekyu Park and Will Epperson and Muhammed Ahmed and Stephane Pinel and Diyi Yang and Duen Horng (Polo) Chau},
year={2020},
eprint={2001.01819},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
		

FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learning
Angel Cabrera, Will Epperson, Fred Hohman, Minsuk Kahng, Jamie Morgenstern, Duen Horng (Polo) Chau
Discovering intersectional ML Bias through interactive visualization.
IEEE Conference on Visual Analytics Science and Technology (VAST). Vancouver, Canada, 2019.
Project Demo PDF Blog Recording Code BibTeX

			
@article{cabrera2019fairvis,
  title={FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learning},
  author={Cabrera, {\'A}ngel and Epperson, Will, and Hohman, Fred and Kahng, Minsuk and Morgenstern, Jamie and Chau, Duen Horng},
  journal={IEEE Conference on Visual Analytics Science and Technology (VAST)},
  year={2019},
  publisher={IEEE}
  url={https://poloclub.github.io/FairVis/}
}
		

Talks

Interactive Data Profiling for Python DataFrames with AutoProfiler and Texture
May 2024PyCON 2024

Dead or Alive: Continuous Data Profiling for Interactive Data Science
October 2023VIS 23: IEEE Visualization Conference

A Declarative Specification for Authoring Metrics Dashboards
October 2023VDS at VIS 23: Visual Data Science Symposium

Leveraging Analysis History for Improved In Situ Visualization Recommendation
June 2022EuroVis 22: Eurographics Conference on Visualization

Strategies for Reuse and Sharing among Data Scientists in Software Teams
May 2022ICSE 22: ACM International Conference on Software Engineering

FairVis
October 2019VIS 19: IEEE Visualization Conference

Honors and Awards

2019PURA: President's Undergraduate Research Award
$1500 research grant to continue work on FairVis project

2016Stamps President's Scholarship
Full ride scholarship given to 40 incoming freshman at Georgia Tech

Mentees

During my PhD, I have had the pleasure of mentoring the following undergraduate and masters students on research projects.

Summer 2021 - Fall 2021 Leijie Wang
Visualization recommendation for python in notebooks using history

Fall 2021 - Spring 2022 Asad Sheikh
Visualization recommendation for SQL using history

Spring 2022 - Spring 2023 Vaishnavi Gorantla
Fact generation from data and presentation as text

Spring 2023 - Spring 2024 Yuqi Zhang
Notebook extension for guided statistical analysis

Summer 2023 - Spring 2024 Allie Feldman
Guided Data Analysis

Teaching

Spring 2023Graduate Teaching Assistant
Carnegie Mellon University, Pittsburgh, PA
Programmable User Interfaces, Instructor: Scott Hudson
Taught recitation, designed assignments for class about UI design and intro HTML, CSS, & Javascript.

Fall 2022Graduate Teaching Assistant
Carnegie Mellon University, Pittsburgh, PA
Interactive Data Science, Instructor: Adam Perer and John Stamper
Graded and office hours for class about using jupyter, visualization, steamlit and related tech for data science.

August 2017 - December 2018Undergraduate Teaching Assistant
Georgia Institute of Technology, Atlanta, GA
Intro to Database Systems (CS 4400), Instructor: Monica Sweat
Designed projects, held office hours and graded for relational databases class.

Service

Reviewer for CHI 2025, VIS 2024, VIS 2023, CHI 2023, VIS 2022, CHI 2022, CSCW 2021, VIS 2021.

Leadership & Activities

January 2019 - May 2020 Student Ambassador
Georgia Institute of Technology Alumni Association
Serve as official representative of the Institute at events/tours for alumni, prospective students, and special guests.

January 2018 - May 2019 Executive Board Member -- Threads Co-chair
Stamps Scholars National Convention 2019
Executive board member of Stamps Scholars National Convention, a 3-day conference with over 700 student attendees. Responsible for 20-person committee that plans and coordinates the different content threads of the convention.

Skills

Programing Languages: Python (Advanced), Javascript/Typescript (Advanced), SQL (Intermediate)
Toolkits, Frameworks, Software: Svelte, React, Pytorch, Scikit-learn, Git, VegaLite, D3
Natural Languages: English (Native), Spanish (Advanced)