Our group conducts research in computer science at the intersection of human computer interaction, machine learning, data science, programming languages, and data management.
Visualization leverages human perception to make (potentially large) data accessible. We are developing new languages and tools for analysis and communication.
Human-Centered Data Science
While computers can help us manage data, human judgment and domain expertise is what turns it into understanding. Meeting the challenges of increasingly large and complex data requires methods that richly integrate the capabilities of both people and machines.
Design for Machine Learning
The increasing use of machine learning techniques allows data scientists to summarize, aggregate, and make predictions about their data. While these techniques may be automated and yield high accuracy precision, they are often black-boxes that limit interpretability and actionable insights. We focus on designing novel techniques and systems to keep data scientists and end-users "in-the-loop".
Recent PublicationsShow all
- Demonstration of the Myria Big Data Management Service
- Visualization of Varying Hierarchies by Stable Layout of Voronoi Treemaps
- Dynamic Client-Server Optimization for Scalable Interactive Visualization on the Web
- Perfopticon: Visual Query Analysis for Distributed Databases
- Voyager: Exploratory Analysis via Faceted Browsing of Visualization Recommendations
- Towards A General-Purpose Query Language for Visualization Recommendation
- High Variety Cloud Databases
- SQLShare: Results from a Multi-Year SQL-as-a-Service Experiment
- What Users Don't Expect about Exploratory Data Analysis on Approximate Query Processing Systems
- Text detection in screen images with a Convolutional Neural Network
- Lessons from Pangloss: User Encounters with Uncertainty
- The Myria Big Data Management and Analytics System and Cloud Service
- Extracting Neighborhood Structure from Very Large DNA Graphs
- Trust, but Verify: Optimistic Visualizations of Approximate Queries for Exploring Big Data
- Vega-Lite: A Grammar of Interactive Graphics
- Voyager 2: Augmenting Visual Analysis with Partial View Specifications
- Altair: Interactive Statistical Visualizations for Python
- Beyond Heuristics: Learning Visualization Design
- Formalizing Visualization Design Knowledge as Constraints: Actionable and Extensible Models in Draco
- Visualizing a Million Time Series with the Density Line Chart
- Exploring neighborhoods in large metagenome assembly graphs reveals hidden sequence diversity
- Value-Suppressing Uncertainty Palettes
- Interactive Systems for Scalable Visualization and Analysis
- Falcon: Balancing Interactive Latency and Resolution Sensitivity for Scalable Linked Visualizations