I'm the Executive Director of Covid Watch, an open source nonprofit I founded in February 2020 with a mission -- build mobile technology to fight the pandemic while defending digital privacy. I was quickly joined by three other founders and our team now has over more than 500 volunteers from around the world including advisers in public health, epidemiology, privacy, policy, and law from universities like Stanford, Waterloo, UW, UCSF, and Berkeley.

The Covid Watch team was the first in the world to publish a white paper, develop, and open source decentralized Bluetooth exposure alert technology in early March. Our TCN Protocol received significant news coverage and led to the development of very similar anonymous protocols like DP3T, PACT, and Google/Apple exposure notifications. Covid Watch volunteers and nonprofit staff also built a fully open source mobile app for sending anonymous exposure alerts.

Technical Projects

Covid Watch puts the power to stop COVID-19 in the palm of your hand.

Covid Watch is an open source nonprofit and privacy watch group for Covid-19 mobile apps. Our mission is to build mobile technology to fight the pandemic while defending digital privacy. 56% adoption of an app that sends exposure alerts would stop community spread. Our research team first discovered and implemented a way to send these alerts anonymously, and the app development team is now made up of hundreds of volunteers. covid-watch.org link Covid Watch github github TCN Protocol github github

A webpage rating button to reward content creators and build an ad-free ecosystem

This is a browser extension that lets you rate any webpage and an associated search engine with confidence scores based on positive and negative emotional valence. I used the same scoring algorithm as reddit's "top" score plus noise to help elevate new webpages. This is an alternative to click-based models to help combat the excessive rewarding of polarizing content. A paid version could reward content creators you have rated positively to help reduce reliance on ads. Demo at Upvote.vote. link

Research Background

I originally worked in aerospace engineering, completing my M.S. at the University of Arizona. While at Honeywell Aerospace, I invented and patented a method for eliminating transonic flutter in turbomachinery, influencing the design of next generation jet engines.

After spending several years in industry, I decided to pursue a PhD at Stanford supported by a Department of Energy Computational Science Graduate Fellowship (DOE CSGF).

At Stanford, I focused on courses in computer science and machine learning. I developed two novel methods for faster and more accurate reduced order models and I designed neural network architectures for approximating the solutions to partial differential equations by breaking them into parts. My long term research goal is to understand how to automatically draw boundaries in spatial and temporal data in a way that is useful for prediction and explanation.

I was also involved with Stanford Effective Altruism and their AI Safety discussion groups. I care about building technology aligned with human rights and values.

Research Highlights

Publications

White, Cristina. Comparing Reduced Order Models and Neural Networks for Predictions from Constrained Aerodynamics Datasets. Stanford. Dissertation In Progress.

Petrie, J. & White, C., et al. "Slowing the Spread of Infectious Diseases Using Crowdsourced Data." Stanford and Waterloo Independent Research Project. Covid Watch White Paper, 2020. paper link link

White, Cristina, et al. "Fast Neural Network Predictions from Constrained Aerodynamics Datasets." AIAA Scitech Forum, 2020. American Institute of Aeronautics and Astronautics, AIAA, 2020. arxiv link paper poster github

White, C., & Farhat, C. & Avery, P. A Spatial Clustering Algorithm for Constructing Local Reduced order Bases for Nonlinear Model Reduction. Presentation at the annual meeting of U.S. National Congress on Computational Mechanics, USNCCM14, Montreal, Canada. July 2017. talk poster talk paper github

White, Cristina. Flutter-resistant transonic turbomachinery blades and methods for reducing transonic turbomachinery blade flutter. EP 2907972A1, European Patent Office, 19 August 2015. link patent

White, Cristina. Flutter-resistant transonic turbomachinery blades and methods for reducing transonic turbomachinery blade flutter. US 20150233390A1, United States Patent and Trademark Office, 14 February 2014. link patent

Seele, Roman, et al. "Some effects of blowing, suction and trailing edge bluntness on flow separation from thick airfoils; computations & measurements." 29th AIAA Applied Aerodynamics Conference. 2011. link paper

White, Cristina. Application of Computational Fluid Dynamics on a Blunt Elliptical Airfoil. Master's Thesis. University of Arizona, 2009. thesis talk

Zakharin, Boris, et al. "The utility of hysteresis for closed-loop control applications that maintain attached flow under natural post stall conditions on airfoils." 4th Flow Control Conference. 2008. link paper

Projects

White, Cristina R. A neural network for breaking time dependent problems into parts. Technical report. CS379C. Department of Mechanical Engineering, Stanford University (2018) paper github

White, Cristina R. A neural network architecture for reduced order modeling of PDEs. Technical report. CS221. Department of Mechanical Engineering, Stanford University (2016) paper poster github

White, Cristina R. Unsupervised Learning of Time-Dependent CFD Solutions using LSTMs. Technical report. CS231N. Department of Mechanical Engineering, Stanford University (2016) paper poster github

White, Cristina R. A reduced order modeling method for improving online computation time and accuracy using mesh coarsening. Technical report. AA290. Department of Mechanical Engineering, Stanford University (2016) paper talk github

White, Tina R. A Clustering Algorithm for Reduced Order Modeling of Shock Waves. Technical report. CS229. Department of Mechanical Engineering, Stanford University (2015) link paper github

Awards

Department of Energy Computational Science Graduate Fellowship. 2016 - 2020 link link

Stanford University Research and Teaching Assistantships. 2015 - 2016.

Honeywell Aerospace Technical Achievement Award. 2015.