Karl Cobbe
Research Scientist at OpenAI
Palo Alto, California, United States
Summary
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Rockstar🎓
Top SchoolKarl Cobbe is a Research Scientist at OpenAI based in Palo Alto with seven years of industry experience and a BS in Computer Science and Artificial Intelligence from Stanford. He progressed from software engineering roles at companies like Art of Problem Solving and Chatous to an OpenAI Machine Learning Fellowship and a Research Scientist role, illustrating a trajectory from product engineering to deep ML research. His background includes early work in applied physics and hardware verification at HP, giving him an uncommon low-level systems perspective that informs his approach to scalable ML systems. Comfortable moving ideas from prototype to production, he brings a blend of rigorous academic training and practical engineering experience to applied AI problems.
8 years of coding experience
3 years of employment as a software developer
Phillips Exeter AcademyBS, Computer Science, Artificial Intelligence, BS, Computer Science, Artificial Intelligence at Stanford University
Github Skills (11)
deep-reinforcement-learning10
pytorch10
benchmark10
openai10
reinforcement-learning10
paper9
deep-learning9
procedural-generation9
procedural8
gradient8
machine-learning1
Programming languages (3)
Github contributions (5)
openai/train-procgen
Dec 2019 - Jun 2020
Code for the paper "Leveraging Procedural Generation to Benchmark Reinforcement Learning"
Contributions:9 commits, 2 PRs, 6 pushes in 5 months
leveragingproceduralreinforcement-learningdeep-reinforcement-learningprocedural-generation
openai/phasic-policy-gradient
Sep 2020 - Dec 2020
Code for the paper "Phasic Policy Gradient"
Contributions:2 commits, 1 push, 1 comment in 3 months
policygradientpolicy-gradientphasic-policy-gradient
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