Large Scale Data Monitoring for Critical Domains via Human-AI Collaboration - Ananya Joshi

Year
2025
Organisation
Carnegie Mellon University
Tags
human-AI collaboration
big data
data monitoring
event detection
public health analytics
prioritization
alert fatigue
extreme value theory
explainable AI
data streams
Summary

This research develops human–AI methods to prioritize massive data streams, especially in public health. By combining expert expectations with extreme value theory, it ranks events by contextual importance, reducing alert overload. Deployed nationally, the approach triaged thousands of outbreaks and data-quality issues, making big data interpretable, actionable, and life-saving decisions.