Associate Professor, University of Massachusetts at Amherst
2 papers at NeurIPS 2025
We present active measurement, a human-in-the-loop AI framework that combines AI predictions with importance sampling, model adaptation, and human labeling to make accurate scientific measurements.
Realistic fine-grained multi-label dataset with evaluation and analysis on SPML methods in multiple data regimes.
