Human Data Interaction Lab

The goal of the Human Data Interaction Lab (HuDa) is to research methods at the intersection of data management, data science, and interactive systems to enable the derivation of insights from data and to support data-driven decision-making. Our approach is human-centric in that we aim to understand how humans at any level of data-literacy (which include analysts, scientists, journalists, researchers, data enthusiasts) interact with data. 

Through this understanding, we build formalizations and systems that that make it easier for humans to effectively interact with data. HuDa, thus, addresses the critical bottleneck in today’s data analysis: this bottleneck is not the lack of data, or our ability to analyze it at scale, but the lack of human cognition and time to build and understand data processes.

The HuDa Interaction Lab has made several research contributions in the following areas:

  • novel querying paradigms for prescriptive analytics
  • example-driven Interfaces for data tasks
  • debugging complex data analytics
  • teaching and democratizing data science

Incidentally, Huda in Arabic means guidance. We hope to build tools that guide humans through better data analysis and data-driven decision-making.

Current Research Projects

  • Synner: Generating Realistic Synthetic Data
  • Scalable Package Queries: Scaling Package Queries over Probabilistic Databases
  • Texture: A Collaborative Framework for Structure Identification over Print Documents
  • Qetch: Expressive Time Series Querying with Hand-Drawn Scale-Free Sketches
  • Seer: Auto-Generating Information Extraction Rules from User-Specified Examples
  • Data-Driven Decision Making in Health: Expressive Time Series Querying with Hand-Drawn Scale-Free Sketches
  • Teaching Query Languages: Using Visual Query Plans and Data to Explain Relational and Graph Queries
  • Epidemic Interventions: Epidemic Policy Optimizations to Control Epidemic Outbreaks


Name Title
Azza Abouzied Principle Investigator; Associate Professor of Computer Science
Miro Mannino Research Engineer
Anh Mai PhD Candidate
Junior Garcia PhD Candidate
Cole Robert Beasley Research Assistant