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  • Universiy of California San Diego
  • United States
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Achievement: Pull Sharkx2Achievement: QuickdrawAchievement: StarstruckAchievement: Arctic Code Vault Contributor

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@aravindr93
Aravind Rajeswaran aravindr93
Research Scientist at Facebook AI Research (FAIR). PhD in computer science from the University of Washington.

Seattle, WA

@hyperopt
hyperopt
@facebookresearch
Meta Research facebookresearch

Menlo Park, California

@google-deepmind
Google DeepMind google-deepmind
@NVlabs
NVIDIA Research Projects NVlabs
@xvjiarui
Jerry Jiarui XU xvjiarui
Part of the journey is the end

UCSD La Jolla

@yzqin
Yuzhe Qin yzqin
Dexterous manipulation for fantastic robots
@RchalYang
Ruihan Yang RchalYang
Ruihan Yang // RL // UC San Diego

UC San Diego La Jolla, San Diego

@vivekmyers
Vivek Myers vivekmyers
@aviralkumar2907
Aviral Kumar aviralkumar2907
@ikostrikov
Ilya Kostrikov ikostrikov

Berkeley

@seohongpark
Seohong Park seohongpark
@ColinQiyangLi
Qiyang (Colin) Li ColinQiyangLi
PhD student @ UC Berkeley
@lucidrains
Phil Wang lucidrains
Working with Attention. It's all we need

San Francisco

@kvfrans
Kevin Frans kvfrans
PhD @ UC Berkeley. Previously at MIT, CrossLabs, Sizigi, Autodesk, OpenAI.

United States

@StoneT2000
Stone Tao StoneT2000
Robot Learning, RL, Simulation. PhD @ UC San Diego. Research Intern @NVIDIA Co-founder @Lux-AI-Challenge.
@karpathy
Andrej karpathy
I like to train Deep Neural Nets on large datasets.

Stanford

@vmoens
Vincent Moens vmoens
Software engineer @ Meta

Meta London

@nicklashansen
Nicklas Hansen nicklashansen
PhD student @ UC San Diego. Interested in reinforcement learning, representations, and robots.

San Diego, CA

@shrivaths16
Shrivaths Shyam shrivaths16
MS ECE @ UCSD

@talmolab San Diego, California

@colah
Christopher Olah colah
I want to understand things clearly and explain them well. Interpretability at Anthropic. Formerly OpenAI, Google Brain.

Anthropic San Francisco

@danijar
Danijar Hafner danijar
Building AI that makes autonomous decisions using world models, artificial curiosity, and temporal abstraction

DeepMind Berkeley