Daniel聽Hernandez
Software Engineer at Google DeepMind
New York, New York, United States
Summary
馃懁
Senior馃帗
Top SchoolDaniel Hernandez is a software engineer and machine learning practitioner with eight years of experience bridging theoretical physics and production ML systems. A Ph.D. in High Energy Physics turned researcher and Google AI Resident, he has shipped models and infrastructure at Google and DeepMind while drawing on deep probabilistic and statistical intuition from his academic work. He programs fluently in Python, C++, Scala and TypeScript, and is comfortable moving research ideas into scalable code and data pipelines. Based in New York, he combines rigorous publication-grade thinking with hands-on engineering practices, often leveraging mathematical methods from physics to design novel ML algorithms.
9 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (Ph.D.) High Energy Physics, Doctor of Philosophy (Ph.D.) High Energy Physics at Universidad Aut贸noma de Madrid
English, Spanish, Italian, French
Github Skills (7)
python9
tensorflow9
machine-learning9
deep-learning9
neural-network8
ml8
deep-neural-networks8
Programming languages (1)
Github contributions (5)
dhernandd/neurolib
Dec 2018 - Mar 2019
Contributions:44 commits, 32 pushes, 13 branches in 3 months
dhernandd/supervind
Feb 2018 - Oct 2018
Contributions:110 commits, 1 PR, 93 pushes in 7 months
tensorflow
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