Joshua Kravitz

Hi, I’m Joshua!

I’m a technologist looking to make a difference.

I lead technology modernization efforts on the U.S. Senate Committee on Appropriations. Before coming to the Senate, I worked on the House Committee on Oversight and Reform through the TechCongress Program, with a focus on IT modernization, customer experience, and data governance.

After graduating in June 2020 from Stanford University with a B.S. in computer science (focus: systems and AI) and M.S. in statistics (focus: causal inference), I dove into the world of political campaigns: I was Deputy Data Director on Jon Ossoff’s campaign for U.S. Senate and Data Director on Sri Kulkarni’s congressional campaign.

While I wasn’t researching new methods for estimating causal effects at Stanford, I oversaw the student leadership team for Camp Kesem at Stanford.

In my free time, I watch TV, read, play jazz piano, bake sourdough, and improvise. To me, improvisation is more than a fun hobby – it’s a way of life. My favorite improv maxims are “Say Yes,” “Follow the Fear,” and “Mistakes are Gifts.”

Interests

Government service delivery
Civic engagement
Progressive analytics
Leadership and management

Education

MS in Statistics (Causal Inference), 2020
Stanford University
BS in Computer Science (Systems), 2018
Stanford University

Recent Posts

Guide to Political Data

I wrote this up for staff on Jon Ossoff for Senate’s Community Mobilizer program and figured I would save it here. The audience is (mostly) people who know about field and want to get into data. This mostly serves as a reference to other quality guides. Relevant Skills Spreadsheets – I avoid them when I can, but they’re often unavoidable. You’ll save yourself some headaches if you know the basics: vlookup, importrange, filter, query.

Last updated on Jan 25, 2021 2 min read

What Is Causality

When I meet new people or talk with friends, many wonder what I mean when I say I’m interested in causal inference. I then go on to give a short pitch on causal inference and observational studies. I figure I’d write down what I say in a blog post. Be warned that I have only been studying this stuff for around a year, so I’m by no means an expert; some of what I say, too, might be oversimplified or plain wrong (hopefully not the case, but if something seems suspect, let me know!

Last updated on Nov 9, 2019 5 min read

My First Post

This is my first post on my new website! I’ve always been hesitant to make a personal website – it has always felt a bit self-centered – but I’ve decided that for now, the pros outweigh the cons. I plan on using this website as a portfolio and record of my work, likely in data analysis but also in any other areas relevant to my experience and goals. Perhaps as time passes, I’ll start jotting notes and thoughts down here as well (no promises).

Last updated on Oct 28, 2019 1 min read

Publications

Robert Lerrigo, Johnny TR Coffey, Joshua L Kravitz, Priyanka Jadhav, Azadeh Nikfarjam, Nigam H Shah, Dan Jurafsky, Sidhartha R Sinha (2019). The Emotional Toll of Inflammatory Bowel Disease: Using Machine Learning to Analyze Online Community Forum Discourse. Crohn’s & Colitis 360.

Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A Shamma, others (2017). Visual genome: Connecting language and vision using crowdsourced dense image annotations. International Journal of Computer Vision.

Ranjay A Krishna, Kenji Hata, Stephanie Chen, Joshua Kravitz, David A Shamma, Li Fei-Fei, Michael S Bernstein (2016). Embracing error to enable rapid crowdsourcing. Proceedings of the 2016 CHI conference on human factors in computing systems.