Scott Emmons
Member Of Technical Staff at Anthropic
San Francisco, California, United States
Summary
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Rockstar🎓
Top SchoolScott Emmons is an AI researcher and engineer with 11 years of experience focused on model safety and alignment, currently a Member of Technical Staff at Anthropic after research roles at Google DeepMind. At DeepMind he developed novel chain-of-thought monitorability metrics and helped integrate them into Gemini’s safety evaluation suite and Frontier Safety Framework, directly shaping model cards for major releases. He co-founded FAR.AI, where he combined fundraising, hiring, and research management to advance the startup’s mission, demonstrating both technical depth and operational leadership. With a PhD in Artificial Intelligence from UC Berkeley and a BS in Math & Computer Science from UNC, he pairs rigorous academic training with applied safety work. An early volunteer teacher in international education projects, he brings a values-driven perspective to high-stakes AI development.
11 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD Artificial Intelligence, Doctor of Philosophy - PhD Artificial Intelligence at University of California, BerkeleyBachelor of Science - BS Mathematics and Computer Science, Bachelor of Science - BS Mathematics and Computer Science at The University of North Carolina at Chapel Hill
Github Skills (29)
imitation-learning10
gymnasium10
toolbox9
algorithms9
sparse8
robotics8
pytorch8
representation-learning8
reinforcement-learning7
supervised-learning7
stable-baselines7
python7
optimization7
hyperparameter-tuning7
pybullet7
Programming languages (4)
Github contributions (5)
scottemmons/rvs
Oct 2021 - May 2022
Reinforcement Learning via Supervised Learning
Contributions:41 commits, 15 pushes, 1 branch in 6 months
reinforcement-learningsupervised-learning
scottemmons/sgm
Mar 2020 - Jul 2022
Sparse Graphical Memory for Robust Planning
Contributions:9 commits, 6 pushes, 1 comment in 2 years 4 months
graphicalmemoryplanningsparse
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