MIT
Evan HubingerMember of Technical Staff, Manager · AnthropicResearcher↗
Researcher
Daniel M. Ziegler
AnthropicMember of Technical Staff
Ziegler led early experiments showing that language models could be trained from human preferences, a direct precursor to reinforcement learning from human feedback. He later worked on practical safety research at Redwood, METR, and Anthropic, connecting alignment methods to tests of increasingly capable models.
Career & education
Current roleAnthropic2024-presentMember of Technical Staff
Anthropic2024-presentPreviously
METR2023-2024Member of Technical Staff
Redwood Research2021-2023Member of Technical Staff
OpenAI2018-2021Member of Technical Staff
METR2023-2024Redwood Research2021-2023OpenAI2018-2021Education
Work and education history is primarily focused on AI-relevant roles and may not be comprehensive.
Citation Trend
Total citations to scholarly work, including research papers, technical reports, books and theses, as recorded by Google Scholar. Each point is a dated snapshot.
citations99,207As of Oct 23, '26
citations+6,275Since last snapshot, Aug 1, '26
Selected contributions
Language Models are Few-Shot Learners
With Tom Brown, Ben Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan and others ·GPT-3 performs tasks from prompts and a few examples without task-specific training.
Based on public sources. If accuracy is important, verify details using the links or references.
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Reviewed August 8, 2026 · Checked for accuracy and new information.
