Hamel Husain
Hamel Husain is a machine-learning engineer who helps teams inspect, debug, and measure AI systems. He previously worked at Airbnb and GitHub. In 2019, he coauthored the CodeSearchNet Challenge with a research team, providing data and evaluation material for finding code through natural-language queries. His later guides address data drift, model-based evaluators, and error analysis. They emphasize examining real outputs and checking whether a measurement matches the intended use. In September 2026, Husain and Shreya Shankar published a joint evaluation FAQ, and they also teach evaluation methods together.
- Works
- 2
Publication numbers from OpenAlex, as of 14 October 2026. Citations and h-index are hidden because this OpenAlex record may be incomplete or mix in other authors.
Timeline
-
Earlier industry work
Machine-learning engineering
Husain worked at Airbnb and GitHub before his current advising and teaching.
-
2019
CodeSearchNet
He coauthors and helps introduce a shared code-search challenge with institutional collaborators.
-
April 2024
Data drift
His guide explains using a classifier to inspect differences between datasets.
-
October 2024
Model judges
His evaluation guide calls for validation against human labels.
-
2025
Error analysis
The field guide connects inspection of outputs with practical changes to an AI product.
-
2026
Joint guidance and teaching
Husain and Shreya Shankar publish an evaluation FAQ and teach the methods.
Sources and credits
Photo: Hamel Husain; image supplied by hamel.dev. License: Not stated by source. Source: hamel.dev. Cropped to a square and resized. Ask us to remove or replace this photo.