Jonathan Raiman
Senior Research Scientist at OpenAI
Palo Alto, California, United States
Summary
🤩
Rockstar🎓
Top SchoolJonathan Raiman is a Senior Research Scientist with 12 years of experience building large-scale AI systems, currently leading reinforcement learning efforts at NVIDIA to automate GPU circuit design and holding concurrent research roles at OpenAI. He brings a strong speech and NLP research pedigree from Baidu USA where he co-created Deep Voice 1–3, advanced Deep Speech 2, and developed one-shot learning and learning-to-search QA methods. Trained in autonomy and aeronautics at MIT and holding a PhD in computer science from Université Paris-Saclay, he combines theoretical depth with production-focused engineering. Based in Palo Alto, he excels at taking novel models from research prototypes to large-scale training runs, and has a demonstrated knack for applying RL to unconventional hardware design problems.
12 years of coding experience
2 years of employment as a software developer
Aeronautics & Astronautics, Autonomy, Masters, Aeronautics & Astronautics, Autonomy, Masters at Massachusetts Institute of TechnologyDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Université Paris-SaclayBachelor of Arts (BA), Mathematics and Physics, 3.65, Bachelor of Arts (BA), Mathematics and Physics, 3.65 at Pomona College
French, Spanish
Github Skills (110)
python10
representations10
deep-learning10
mnist10
representation-learning10
sentiment-analysis10
lstm10
paper10
computer-vision10
dropout10
gru10
reinforcement-learning10
automatic-differentiation10
sentiment10
tensorflow10
Programming languages (10)
Github contributions (5)
mlforsystems/mlforsystems.github.io
Sep 2018 - Oct 2021
Workshop on ML for Systems at NIPS 2018 Date December 8th, 2018
Contributions:174 commits, 169 pushes, 1 branch in 3 years 1 month
machine-learning
JonathanRaiman/PVDM
Sep 2014 - Mar 2018
:books: Implementation of Q.V. Le, and T. Mikolov, "Distributed Representations of Sentences and Documents ICML", 2014.
Contributions:9 commits, 1 PR, 2 pushes in 3 years 6 months
nlpdistributed-representationsrepresentationssentencesmachine-learning
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