The Gates Foundation Grand Challenges has teamed up with InfoVision in order to develop a point-in-time first encounter analysis and bias report regarding their current blind review methodology.

First-encounter analysis and Bias Report

With the use of BI tools, the Grand Challenges team is able to develop descriptive reports across multiple areas within said applications. There is currently a lack of a predictive centric environment, where executives can review a point-in-time reflection on the health of the Grand Challenges program. The InfoVision team will provide a executive summary on whether the blind review methodology generates new organizations not originally working with the Bill and Melinda Gates Foundation. Along with this first-encounter analysis, we will take a look into whether there are any biases in the triage process. This includes but is not limited to: grammatical and syntax errors, primary language, and gender. With Grand Challenges being the only Gates Foundation team that is looking into their own biases, we hope that this may trickle out and be a golden standard for other teams.

InfoVision Team

Sponsor: Zach Charat


Collin Frietzsche

Java, Python, R, MS SQL Server, TippingPoint, Wireshark, Kali linux

Juan Alvarez

Data science track familiar with: Java, R, Python, SQL, Visual Basic.NET, Arduino, and MATLAB

Madeline Holmes

React, Javascript, Java, HTML/CSS, R, Python, SQL, PowerBI

Nick Olds

Java, HTML/CSS, MySQL, PostgreSQL, React, JavaScript, PHP, R, VB.NET, AWS

How to Reach Us

Collin Frietzsche (collinaf@uw.edu)

Juan Alvarez (juania1@uw.edu)

Madeline Holmes (mholmes2@uw.edu)

Nicholas Olds (oldsn@uw.edu)

We would love to hear from Gates Foundation executives and application users in order to get more feedback on the project. This may include but is not limited to: testers, designers, users, and developers.