projects

real job (2019 - present)

For the last 6 years I've been working on the recommendations team at Twitch. We've been responsible for personalizing the entire presentation on the homescreen and leftbar. I've been doing direct work and also the good ol' talking to adults to get things done together. Honestly, my fav part is training and mentoring younger team members... that academic prof in me never really left (for better or for worse xD)...

minimum viable experiment series (I do that once in a while)

Like single file experiments to trully grok things? I got you with Reinforcement Learning and Evolution Stratagies tutorials.

generative models and unsupervised learning for videos (2013 - 2017)

I wrote Recurrent Winner-Take-All and Perception Updating Networks. Those methods show how to learn features by exploiting temporal context and to predict future frames in a video (think video compressor or robot planning).

subpixel (2017)

Enhance! A neural network for image superresolution. This project hit the front page of Hacker News and Trending on Github.

pymerkletools (2018)

I love bitcoin and blockchain! I wrote Tierion's pymerkletools for creating Merkle trees, generating merkle proofs, and verification of merkle proofs.

learning a driving simulator (2016)

I trained generative adversarial and recurrent neural networks to simulate highway videos.

self coloring books (2016)

A segmentation network for self driving car data pipeline

deep learning for self-driving cars (2016)

CNN+RNN model for deciding where the car should go during Summer at comma.ai

EEG analysis for Brain Machine Interface (2015)

I wrote the CSP pipeline for EEG analysis in Theano and fine-tuned everything end-to-end. I could've won BCI competition 2 T_T

Information Theoretic Learning Autoencoders (2016)

I want to use deep information theoretic learning to compress and make images look pretty.

RGB-D object recognition (~2015)

I trained convnets to recognize objects in 3D when interning with Paracosm.io

ECG analysis (~2014)

My undergrad and master research was on blind source extraction. We had ECG recordings from a pregnant woman and we had to separate the ECG signal of the fetus from the signal of the woman. I used kernels methods back then. You kids don't know that anymore, but kernels used to be cool.

Keras contributor

Keras' community is awesome! I contribute with both Tensorflow and Theano code to the source. Some advanced contributions include Neural Turing Machines and Spatial Transformer Networks.

Hubot Recognizer (~2015)

I put some deep learning on Slack

deep learning with python

video course about deep learning. Mostly using Keras and Theano.

publications

papers, in the end of the day I write machine learning papers for a living