Si Wu

I am a Ph.D. student studying political science at Boston University. I previously completed a master's degree in journalism at Northeastern University, and a bachelor's degree in physics at Imperial College London, U.K.

During the summer of 2019, I worked for the Voting Rights Data Institute, where I conducted research in the mathematics of gerrymandering by applying data science to social and political problems. While there, I coauthored "Geometry of Graph Partitions Via Optimal Transport", a paper supervised by Justin Solomon at MIT.

Prior to that, I was a data researcher for Northeastern's School of Journalism. A highlight of my experience there is a Twitter sentiment analysis project - "Democrats 'went low' on Twitter leading up to 2018" - that got published on news publication Roll Call.

At Imperial College London, I conducted various computing, laboratory and research projects collaboratively and solved challenging physics, math and statistical questions. My experience studying and working in the U.K., China and the U.S. has also provided me with a global perspective, a valuable skill in today’s highly-interconnected world.

Outside my work, I like to cook, box, cycle, and travel.

Publications

Geometry of Graph Partitions via Optimal Transport. SIAM Journal on Scientific Computing. (With Tara Abrishami, Nestor Guillen, Parker Rule, Zachary Schutzman, Justin Solomon, and Thomas Weighill.)

Democrats "went low" on Twitter leading up to 2018. Roll Call. (With Aleszu Bajak.)

Curriculum Vitae

Curriculum Vitae

Data Science Projects

 

 

 

 

 

 

 

 

Media Coverage

Democrats who won 2018 midterms were more negative than Republicans on Twitter, research finds

Si Wu, Journalism graduate student, uses data to help others understand political redistricting

 

Journalism Projects

Roll Call

Democrats "went low" on Twitter leading up to 2018: An analysis of tweets from candidates running for Senate leading up to Election Day

WGBH

Renewable energy is the future. So why are we still stuck in the past?

Global Investigative Journalism Network

How machine learning can (and can't) help journalists

Storybench

The future of machine learning in journalism

Carlos Scheidegger on why data science needs to be done humanely

Takeaways on being a watchdog reporter from the 2018 Boston Watchdog Workshop

How Florida Today created an augmented reality rocket launch app

Foreign Observer

A Chinese student's daunting school experience and what we can do about it

The Scope

Innovative solutions to curb the gun violence epidemic

NU Sci

Commentary: How the use of drones can help us study atmospheric chemicals

Does Climate Change Really Trigger Earthquakes?

How the conflict between science journalism and industry could be exacerbated in today’s media-space

I, Science

New research links diet drinks to weight gain

The Milky Way could contain at least 100 billion brown dwarfs

WordPress

Boston’s sea levels will probably rise by 9 inches as soon as 2030, and here’s what residents and experts say

Q&A: Suzanne Matson on “Ultraviolet,” American womanhood and her family history

A European perspective: Oxford professor Gideon Henderson on ways to mitigate climate change

How "Love Actually" breaks the generic rom-com tradition

How my miserable teaching experience reflects fundamental issues in the British teacher training system

Who’s in charge of your life – you or your phone? It’s up to you to decide.

Teaching: finding moments of happiness in an otherwise grueling experience

Video

An employee of Clover Food Lab talks about its mission, service and recipes

Audio

Ears to the pavement: What Bostonians are saying about the 2018 midterm elections

Photo

Mission Hill 100 Instagram Essay