Will Epperson
YOU?
Author Swipe
View article: Interactive Debugging and Steering of Multi-Agent AI Systems
Interactive Debugging and Steering of Multi-Agent AI Systems Open
Fully autonomous teams of LLM-powered AI agents are emerging that collaborate to perform complex tasks for users. What challenges do developers face when trying to build and debug these AI agent teams? In formative interviews with five AI …
View article: Texture: Structured Exploration of Text Datasets
Texture: Structured Exploration of Text Datasets Open
Exploratory analysis of a text corpus is essential for assessing data quality and developing meaningful hypotheses. Text analysis relies on understanding documents through structured attributes spanning various granularities of the documen…
View article: Guided Statistical Workflows with Interactive Explanations and Assumption Checking
Guided Statistical Workflows with Interactive Explanations and Assumption Checking Open
Statistical practices such as building regression models or running hypothesis tests rely on following rigorous procedures of steps and verifying assumptions on data to produce valid results. However, common statistical tools do not verify…
View article: A Declarative Specification for Authoring Metrics Dashboards
A Declarative Specification for Authoring Metrics Dashboards Open
Despite their ubiquity, authoring dashboards for metrics reporting in modern data analysis tools remains a manual, time-consuming process. Rather than focusing on interesting combinations of their data, users have to spend time creating ea…
View article: Dead or Alive: Continuous Data Profiling for Interactive Data Science
Dead or Alive: Continuous Data Profiling for Interactive Data Science Open
Profiling data by plotting distributions and analyzing summary statistics is a critical step throughout data analysis. Currently, this process is manual and tedious since analysts must write extra code to examine their data after every tra…
View article: Dead or Alive: Continuous Data Profiling for Interactive Data Science
Dead or Alive: Continuous Data Profiling for Interactive Data Science Open
Profiling data by plotting distributions and analyzing summary statistics is a critical step throughout data analysis. Currently, this process is manual and tedious since analysts must write extra code to examine their data after every tra…
View article: Leveraging Analysis History for Improved In Situ Visualization Recommendation
Leveraging Analysis History for Improved In Situ Visualization Recommendation Open
Existing visualization recommendation systems commonly rely on a single snapshot of a dataset to suggest visualizations to users. However, exploratory data analysis involves a series of related interactions with a dataset over time rather …
View article: Strategies for reuse and sharing among data scientists in software teams
Strategies for reuse and sharing among data scientists in software teams Open
Effective sharing and reuse practices have long been hallmarks of proficient software engineering. Yet the exploratory nature of data science presents new challenges and opportunities to support sharing and reuse of analysis code. To bette…
View article: Strategies for Reuse and Sharing among Data Scientists in Software Teams
Strategies for Reuse and Sharing among Data Scientists in Software Teams Open
Effective sharing and reuse practices have long been hallmarks of proficient software engineering. Yet the exploratory nature of data science presents new challenges and opportunities to support sharing and reuse of analysis code. To bette…
View article: FAIRVIS: Visual Analytics for Discovering Intersectional Bias in Machine Learning
FAIRVIS: Visual Analytics for Discovering Intersectional Bias in Machine Learning Open
The growing capability and accessibility of machine learning has led to its application to many real-world domains and data about people. Despite the benefits algorithmic systems may bring, models can reflect, inject, or exacerbate implici…
View article: FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learning
FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learning Open
The growing capability and accessibility of machine learning has led to its application to many real-world domains and data about people. Despite the benefits algorithmic systems may bring, models can reflect, inject, or exacerbate implici…