Jesse Dodge is a Senior Research Scientist at the Allen Institute for AI with 13 years of experience building and evaluating large language models and championing reproducibility and transparency in NLP research. He led evaluation work for OLMo models and has driven efforts to document web-scale training datasets, quantify the environmental and equity costs of AI, and improve experimental rigor across the field. Creator of the widely adopted NLP Reproducibility Checklist and an organizer of the ML Reproducibility Challenge, Jesse blends hands-on model development with community-facing standards that influence major conferences and thousands of papers. His work spans model efficiency techniques such as compression and training optimizations, and has earned long-term recognition including a ten-year Test of Time award at ACL. Based in Seattle, he holds a PhD from Carnegie Mellon and is known for pairing deep technical contributions with practical tools and policies that make AI research more accountable.
13 years of coding experience
3 years of employment as a software developer
Bachelor of Science - BS Computer Science Statistics, Bachelor of Science - BS Computer Science Statistics at University of Washington
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Carnegie Mellon University
Contributions:108 pushes, 1 branch in 1 year 1 month
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