David Dao
daviddao at broad.mit.edu
PhD candidate at ETH Zurich | UC Berkeley | MIT Broad
I'm a PhD student at ETH Zurich DS3Lab, building privacy-preserving and scalable Blockchain + AI systems for sustainability and medicine. Currently I'm a resident at Berkeley AI Research (BAIR) and Oasis Labs. Before joining ETH Zurich, I was a self-driving car engineer in Silicon Valley and a graduate student at MIT Broad Institute. I'm a Global Shaper at World Economic Forum and the founder of Germany's largest machine intelligence meetup, Harvard University's refugees and education conference and Silicon Valley's selfdriving AI series. My work was featured in MIT Technology Review, The Scientist and The New York Times.


Research · Research Blog

Trustless Machine Learning
Data Valuation: How much is your data worth? · Joint project with UC Berkeley
DataBright: Using smart contracts to democratize data and machines
Data Systems for Sustainability
GainForest: Deforestation markets of the Amazon Rainforest using satellite imagery · Microsoft AI for Earth Grant · Grand Prize UNFCCC Hack4Climate at COP23
Data-driven planning and traffic prediction for self-driving cars · Joint project with Mercedes-Benz Research
Privacy-Preserving Systems for Medicine
Kara: A privacy-preserving tokenized data market for medical data · Joint project with UC Berkeley
Cyto.ai: Interactive machine learning for cell biology · Joint project with Broad Institute of MIT and Harvard

Publications · Google Scholar

Manuscripts

“How Much is My Data Worth?”: Data Valuation with Efficient Shapley Value Estimation
DataBright: Towards a global exchange for decentralized data ownership and trusted computation

2018

A Demonstration of Sterling: A Privacy-Preserving Data Marketplace

2017

An open-source solution for advanced imaging flow cytometry data analysis using machine learning

2016

CellProfiler Analyst: interactive data exploration, analysis and classification of large biological image sets

2015

Anatomy of BioJS, an open source community for the life sciences

2014

Automated Plausibility Analysis of Large Phylogenies

Open Source · Github

Almost all of my work is open source

· Awful-AI😈 is a curated list to track current scary usages of AI - hoping to raise awareness
· Awesome-Deep-Learning🔥 is a curated list of papers and code about very deep neural networks
· Spatial Transformer is part of TensorFlow Models (where I'm co-author)
· CellProfiler Analyst is an adaptive machine learning tool for biologists
· BioJS is an interactive visualization ecosystem for life science


You can follow me on Twitter at @dwddao.