About

Hey! I'm Jeffrey (he/him/他). I'm a student at MIT studying computer science and urban planning, with a minor in political science. I want to use technology to bring clarity and transparency to politics, and am especially interested in data journalism, city planning, open source software, and civic tech.

I'm currently doing research in the MIT Media Lab's City Science Group, as well as the MIT Political Science Department, and am a volunteer data analyst for Sri Kulkarni's 2020 Congressional campaign. I also run a blog and a micro-blog, where I write about data visualization, politics, and more!

Portfolio

Research

Jan 2020 - Present

LobbyView

Developing interactive data visualizations using D3 and React for LobbyView, a database of Congressional lobbying that aims to facilitate political science research and bring transparency to money in politics.

Fall 2018

Russian Internet Disinformation

Used machine learning and sentiment analysis to explore Russian disinformation on Twitter in the 2016 and 2018 elections. Wrote an interactive data journalism series and created a (now defunct) Twitter bot. Completed as part of an Independent Project at Phillips Academy with R. Miles McCain, under the mentorship of John Palfrey, Michael Barker, and Malgorzata Stergios.

Fall 2018

Deciphering Chinese Censorship

Developed the Weibo Censorship Dashboard, a nearly real-time, fully open-source feed of censorship on the popular Chinese social media site Weibo. Published paper on SSRN. Completed as part of an Independent Project at Phillips Academy with R. Miles McCain, under the mentorship of John Palfrey, Michael Barker, and Malgorzata Stergios.

Politics

Jan 2020 - Present

Bluebonnet Data Fellow

Volunteer data analyst, using Python and GIS to help down-ballot, Democratic candidates win in swing districts. Currently working with Sri Kulkarni's campaign for the U.S. House of Representatives.

2018

Is My District Gerrymandered?

Created an interactive website that estimates how gerrymandered a U.S. congressional district is, using geometry and election results. Project won the 2018 Congressional App Challenge in Massachusetts's 6th District.

Spring 2018

Exploring the Seats-Votes Curve

Developed an interactive, data-driven explainer of the seats-votes curve, a measure of fairness in redistricting. Built with D3.

Data Visualization

Spring 2019 - Present

Blog

A data visualization publication covering politics, society, and culture. Example topics include mapping the inequal access to shade in Greater Los Angeles and quantifying how lyrical modern hip-hop is.

Summer 2020

Amazon Ring's Police Partnership Tracker

Created a website monitoring the over 1,400 partnerships Amazon Ring has with local law enforcement. Built with Node.js, D3, and MongoDB.

Spring 2018

State of the Academy

Created a website of interactive visualizations showing the results of The Phillipian's State of the Academy survey, an annual survey covering politics, academics, wellness, and culture at my high school. Built with D3.

Full Stack Development

Spring 2019

PollPA