CHRISTINE CHUNG

Hello World

Hi, I'm Christine. I'm a graduate of the University of Chicago Harris School's MS program in Computational Analysis and Public Policy. I'm happiest working on issues at the intersection of tech, policy, and social justice.

As a programmer, I'm interested in using code and data to solve social and civic problems with human impact. I'm currently a Data Scientist at Meetup where I study communities and help bring people together in real life.

In previous lives, I was an international development project coordinator for Education Development Center, a climate change organizer for the Union of Concerned Scientists, an agricultural intern on a vegetable farm, and an apprentice builder of solar hot air panels. In 2013, I spent the better part of the year in Xi'an, China as a Fulbright-Hays Scholar.

When I'm not at my computer, I like to be far, far away from my computer. That usually means hiking, camping, or just being outdoors.

Selected Projects

• Johnson County Data-Driven Justice

  Data Science & Policy | Winter 2017
  As part of President Obama's Data-Driven Justice Initiative, we are working with the Johnson County, KS, criminal justice system to identify at-risk individuals to receive increased social services.

  Python, Pandas, SKLearn, Postgres/PostGIS, Shapely, Fiona | Github Coming Soon
  Co-Investigator: Alden Golab

• Detecting Unusual Trends in University Energy Usage

  Data Analysis & Visualization | Spring 2016
  In collaboration with the University's facilities department, this project was designed to help the university detect anomalous energy usage patterns in historical energy data, with the potential to detect events in real time. Implemented an algorithm to detect unusual periods of activity in energy time series data using markov models.

  Python, Pandas, Postgres, ElasticSearch | Code , Slides, Report

• Detecting Bias in Police Complaints with Machine Learning

  Data Science & Policy | Spring 2016
  This project sought to detect potential bias in police investigations using differentiated feature sets with supervised machine learning. The project tested the hypthesis that the inclusion of complainant demographic data would boost the predictive abilities of modeling the outcome of police misconduct complaints in Chicago.

  Python, Pandas, SKLearn, Postgres, PostGIS, Matplotlib, NetworkX, Google Maps API | Code, Report

• Meet Halfway

  Web Development | Winter 2016
  Meet Halfway finds mutally convenient meeting destinations based on starting locations, travel methods, and preferred meeting location type. The platform preserves privacy so that you can meet friends, strangers, or acquaintances without revealing your address. Suggestions are provided with fairness scores and approximate travel times to help inform your decision. Meet Halfway currently works for addresses within the United States.

  Django, Postgres, Bootstrap, JavaScript, Google Maps API | Code , www.meethalfway.io

• Visualizations

  Choropleth Map % Population with Reliance on Clean Fuels January 2016 | Created for the Chicago Policy Review Made with JavaScript in Leaflet and data from WHO. See it on on bl.ocks.org or check out the data and code.

Talks, Events, & Resources

• Chi Open Data Sets

  Curated a list of open data sets scraped, cleaned, and/or FOIA'd by Chicago, for Chicago.
  Check it out on Github.

• South Side Civic Scope-a-thon, October 2016

  As co-president of South Side Civic, a CAPP-student led group at UChicago, I helped organize the second annual Civic ScopeAthon. Part hackathon, part case competition, the Civic ScopeAthon's main objective is to help students learn problem scoping skills while competing to solve data and technology challenges for local civic organizations.
  Check out our problem scoping worksheet on Google.

• Markdown and LaTeX, April 2016

  This workshop was designed for policy students at the University of Chicago. The goal was to introduce students to Markdown and LaTeX for easier and prettier report generation.
  Find the slides on Github.

• Python 101 for Policy - Mob Programming, July 2016

  This introductory workshop was designed for policy professionals in the Mayor's Office of Chicago. The goal was for participants to gain a basic understanding computer programming and how it can be used in a policy setting. Participants successfully wrote FizzBuzz by the end of the workshop.
  Find the slides on Google.

Find me elsewhere...

Read my tweets, peruse my GitHub, or check out my LinkedIn, if you're into that stuff.

Or, you can send me an email at cszchung [at] gmail [dot] com.