Denny Britz - Chief Technology Officer at Runloop

Denny Britz

Chief Technology Officer at Runloop

Tokyo, Japan

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Summary

🤩

Rockstar

🎓

Top School

Denny Britz is a CTO and machine learning engineer with 13 years of experience building production-grade AI systems, distributed infrastructure, and high-frequency trading platforms. He led research and open-source engineering at Google Brain (co-authoring several papers and contributing the widely used seq2seq framework) and has founded or CTO’ed multiple startups, most recently Runloop, which trains autonomous agents for DeFi. His background spans deep learning (reinforcement learning, MT, conversational models), scalable data pipelines (Spark, Kafka, Kubernetes) and probabilistic knowledge extraction (DeepDive), giving him rare fluency across research, product and ops. A prolific open-source contributor, his repos include practical RL tutorials and from-scratch neural net implementations that reflect a strong emphasis on teaching and reproducible research. Fluent in international environments after long stints across Asia and Europe, he pairs academic pedigree (Stanford, Berkeley) with hands-on startup execution.

13 years of coding experience

8 years of employment as a software developer

Bachelor of Science (BSc), Electrical Engineering & Computer Science, Bachelor of Science (BSc), Electrical Engineering & Computer Science at University of California, Berkeley

Master's degree, Computer Science, Master's degree, Computer Science at Stanford University

English, German, Japanese, Korean

Github Skills (42)

javascript10

spark10

data-pipelines10

python10

css10

openai-gym10

machine-learning10

data-serialization10

rnn-model10

recurrent-neural-networks10

n10

text-classification10

reinforcement-learning10

java10

regularization10

Programming languages (15)

JavaC++RustScalaGoHTMLSvelteJupyter Notebook

Github contributions (5)

dennybritz/rnn-tutorial-rnnlm

Sep 2015 - Dec 2022

Recurrent Neural Network Tutorial, Part 2 - Implementing a RNN in Python and Theano

Role in this project:

Data Scientist

Contributions:42 commits, 16 PRs, 37 pushes in 7 years 4 months

Contributions summary:Denny's commits focused on implementing a Recurrent Neural Network (RNN) for language modeling using Python and Theano. They worked on data loading, preprocessing, and building the RNN model. Key contributions include defining the RNN architecture, forward propagation, loss calculation, and implementing the backpropagation through time (BPTT) algorithm. The user also performed gradient checks to validate the implementation.

rnnpythondeep-learningtheanoneural-networks

dennybritz/neal-react

Sep 2015 - Apr 2018

Startup Landing Page Components for React.js

Role in this project:

Front-end Developer

Contributions:130 commits, 10 PRs, 78 pushes in 2 years 7 months

Contributions summary:Denny primarily contributed to the implementation and styling of React.js components for a startup landing page. Their commits show modifications to the `js/bundle.js` file, which includes code differences related to the styling of components such as the footer, signup form and a sample page. Furthermore, the user added a new feature and updated the footer component by adding social icons. These changes indicate a focus on the user interface and overall design elements of the landing page.

react-jsreact

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