Thomas Glen Dietterich
Thomas Glen Dietterich studies how machines learn from experience and how AI systems can recognize their limits. His work includes supervised and reinforcement learning. Dietterich earned his Stanford doctorate in 1984 and joined the Oregon State faculty in 1985. With Jude Shavlik, he published Readings in Machine Learning in 1990. His work includes error-correcting output codes, multiple-instance learning and hierarchical reinforcement learning. He co-founded the free electronic Journal of Machine Learning Research in 2000 and led the NIPS conference that year.
- Now at
- Oregon State University
- Works
- 310
- Citations
- 40,211
- h-index
- 65
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
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1984–1985
Stanford and Oregon State
Dietterich earned his Stanford doctorate in 1984 and joined the Oregon State faculty in 1985.
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1990
A machine-learning research collection
With Jude Shavlik, he published Readings in Machine Learning in 1990. His work includes error-correcting output codes, multiple-instance learning and hierarchical reinforcement learning.
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2000
Open research publication
He co-founded the free electronic Journal of Machine Learning Research in 2000 and led the NIPS conference that year.
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As of October 2026
Robust learning systems
His research includes detecting unfamiliar images, estimating performance guarantees and identifying failed environmental sensors. A continuing aim is to construct AI systems that recognize their limitations.
Sources and credits
Photo: Oregon State University, via Wikimedia Commons. License: CC BY-SA 2.0. Source: commons.wikimedia.org. Cropped to a square and resized. Ask us to remove or replace this photo.
