David Dao
daviddao at broad.mit.edu
PhD student at ETH Zurich | Past: Stanford, Berkeley, MIT
I'm a Ph.D. student at ETH Zurich building AI and Data Systems for Sustainable Development.
I'm leading the machine learning for climate action research at DS3Lab, mapping the ethical use of AI, and directing the Kara research project with Stanford and UC Berkeley, aiming to build a privacy-preserving data market for medical research. Furthermore, I'm the founder of GainForest, an award-winning non-profit which leverages decentralized technology to prevent deforestation. Previously, I was an engineer in Silicon Valley and a research fellow at Berkeley AI Research (BAIR), Stanford University and Broad Institute of MIT and Harvard. I'm a Global Shaper at World Economic Forum, a Climate Leader at Climate Reality Project, and organized conferences with thousands of attendees in Germany, Silicon Valley, and at Harvard.
๐Ÿ—ž๏ธ Media features:
GainForest featured in MIT Technology Review, Microsoft, United Nations
Kara featured in WIRED, The New York Times, MIT Technology Review
Ethical AI featured in digitalculture.la
Previous research at MIT featured in The Scientist

๐Ÿ‘‡ In short for millenials:
PhD student @DS3Lab. AI to Sustainable Development ๐Ÿง โš•๏ธ
Founder @GainForest. Using ๐Ÿ›ฐ and ๐ŸŽฎto restore ๐ŸŒด
Goal: Save the world with tangible technology ๐ŸŒ
Academic: ETH, Past: Stanford, Berkeley, MIT


โœˆ๏ธ I'm traveling...

Research ยท Medium Blog

Want to work on the UN's Sustainable Development Goals (SDGs) and finish your thesis at the same time? Here are some thesis proposals!



Safe & Trustworthy Machine Learning
Data Valuation: How much is your data worth? ยท Joint project with UC Berkeley
DataBright: Using smart contracts to democratize data and machines
Machine Learning Systems for Climate Action
Deforestation prediction of the Amazon Rainforest using satellite imagery ยท Microsoft AI for Earth Grant ยท Grand Prize UNFCCC Hack4Climate at COP23 ยท Presentation at COP24
Machine Learning Systems for Good Health and Well-Being
Kara: A privacy-preserving tokenized data market for medical data ยท Joint project with UC Berkeley and Stanford
Piximi: Interactive machine learning for cell biology ยท Joint project with Broad Institute of MIT and Harvard
Deep Prediction: Data-driven planning and traffic prediction for self-driving cars ยท Joint project with Mercedes-Benz Research
Machine Learning Systems for Quality Education
Tiny Turing: Interactive machine learning for creative story-telling

Publications ยท Google Scholar

2019

GeoLabels: Towards Efficient Ecosystem Monitoring using Data Programming on Geospatial Information
Data Capsule: A New Paradigm for Automatic Compliance with Data Privacy Regulations
Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms
GainForest: Scaling Climate Finance for Forest Conservation using Interpretable Machine Learning on Satellite Imagery
Towards Efficient Data Valuation Based on the Shapley Value

2018

DataBright: A Data Curation Platform for Machine Learning based on Markets and Trusted Computation
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 Software ยท Github

Almost all of my work is open source

profile for David Dao on Stack Exchange, a network of free, community-driven Q&A sites

Star ยท Awful-AI ๐Ÿ˜ˆ is a curated list to track current scary usages of AI - hoping to raise awareness
Star ยท Awesome-Deep-Learning ๐Ÿ”ฅ is a curated list of papers about very deep neural networks
Star ยท Spatial Transformer ๐ŸŒ is part of TensorFlow Models (where I'm co-author)
Star ยท CellProfiler Analyst ๐Ÿ”ฌ is an adaptive machine learning tool for biologists
Star ยท Green Artificial Intelligence Standard ๐ŸŒฑ aims to develop a standard and raise awareness for best environmental practices in AI research and development
Star ยท BioJS ๐Ÿ”ฌ is an interactive visualization ecosystem for life science

Scientific Collaborators

I'm grateful to work with my scientific collaborators

ยท Dawn Song, Ruoxi Jia (UC Berkeley)
ยท Robert Chang (Stanford Medicine)
ยท Anne Carpenter, Allen Goodman (MIT Broad Imaging Platform)
ยท Joe Near (University of Vermont)
ยท Yan Meng (Mercedes-Benz Research)

Former/Current Students

I'm proud of my students

ยท Levin Moser (ETH)
ยท Catherine Cang (UC Berkeley)
ยท Ming Zhang (ETH)
ยท Luca Lanzendorfer (ETH / Now at Mercedes-Benz Research)
ยท Florian Chlan (ETH / Now at Amazon)
ยท Nino Weingart (ETH)
ยท Christopher Friedrich (Reutlingen / Now at MIT)

Scientific Service / Consulting

Active member of the scientific community and several think tanks

ยท Program Committee NeurIPS Climate Change AI'19
ยท Reviewer ISC-HPC'15


You can follow me on Twitter at @dwddao.