Matthew McAteer

Matthew McAteer

Scientist. Developer. Lifelong learner.

Lifelong learner.




Private ML for Biomedical Research (Pioneer Winner)

Evolution Sim

Evolutionary Algorithm Sim (Tensorflow.js)

Tensorflow Probability

Tensorflow Probability


HelloFriend (Federated ML for social media)

Censorship-Resistant Journalism

Inkrypt (IPFS/IPNS engineering for censor-resistant journalism)

Distributed Mask R-CNN

Distributed Mask R-CNN (PyTorch implementation)

PySpark Udemy Course

PySpark Udemy Course (4.8/5.0 avg review)

Ethereum Tic-Tac-Toe

Ethereum Tic-Tac-Toe (got shoutout from Siraj Raval)

Distributed AI Marketplace

ML Model Marketplace (featured by iExec Team)

OpenMined Mask R-CNN

OpenMined (PySyft, Grid, & Adapters contributor)

PyKafka (Apache Kafka for Python)

Apache Kafka Python bindings (contributor)

Hallite II from Two Sigma (Top 9%)

Hallite II from Two Sigma (Top 9% for best bot)

MIT Policy Hackathon (Track Winner)

MIT Policy Hackathon (Track Winner)

Memorial Sloan Kettering (Kaggle)

Cancer Mutation Classifier (Data from MSKCC)

Medium ML Career Guide

ML Career Guide ( series @ Towards Data Science)


Face-GAN (trained on 200K-image CelebA dataset)

Hints, but not solutions

Project Euler hints (no answers, that'd be cheating)

Bayesian Bitcoin Bot

BTC Price Predictor (based on Shah, Kang; 2014)

Visual Cortex Mapping

Visual Cortex Mapping (Hyman Lab)

EV Decision Support

EV Decision Support (Karp Lab)


BearCoin (Hack@Brown 2015)

MEG Data Classifier

MEG Data Classifier


DeDay (Undergrad Research)


MIT CECI (Robotics iLab Project)

caDNAno (pre-alpha)

caDNAno (high school intern)

     Hi, I'm Matt, a machine learning engineer and data scientist who loves finding solutions to problems of data analysis (which turns out to be most problems). I am applying the skills I gained from years in genomics research and neurology research to private machine learning and automated data science tools. In my spare time, I am involved in the DIY synthetic biology movement, and I write scripts for algorithmic trading and multi-agent game-playing bots.

    On the practical front, I am a focused, results-oriented, and enthusiastic person. Being an active member of the Cambridge-area biohacker community, hackathon teams, as well as numerous research groups at Brown University, MIT, and Harvard Medical School, imbued the importance of working well with others. Team cohesiveness is critical to the success of any company or research group.

    I’m looking to apply my skills and efforts to any group working toward a brighter future. I am especially keen on areas such as community-building, age-related disease research, distributed applications, data science and artificial intelligence, and bridging the gap between our technological and cultural reaches.

    As an engineer, I want to help people overcome fuzzy human protocols and leverage technology to make the world a better place. As a scientist, I’m interested in finding tools for the engineers of tomorrow to use.

    As a leader, I believe that all humans have the potential to make a lasting and positive impact on the world. I believe that positivity, altruism, optimism, and autodidactism are the best traits to strive for. I believe that despite the archetype of the lone genius, the biggest advances and paradigm shifts are made when we band together and pool our talents.

See My Resume