2021 Data Science for Social Good
The Data Science for Social Good summer program trains aspiring researchers to work on data science projects with social impact. Working closely with governments and nonprofits, participants take on real-world problems in education, health, energy, public safety, transportation, economic development, international development, and more. Participants include a diverse and inclusive cohort of students who spend the summer on campus working with the program.
This third summer of the Stanford Data Science for Social Good (DSSG) program ran from June 21st to August 13th, 2021.
The goal of the DSSG program is to train the next generation of ethically aware data scientists and to provide measurable impact for projects with social impact. This summer's program had nine student fellows from a variety of backgrounds, ranging from computer science to statistics to sociology. This year, Stanford also invited fellows from other US universities! The fellows divided into three teams, each worked with a different partner organization to bring critical insights into a core data science challenge.
- View the intro to the program and all final presentations (Final Presentations were Wednesday, August 11, 2021 from 10:00 - 11:30 am)
Forecasting Aids for COVID-19 Research
The Delphi Research Group at Carnegie Mellon University is one of two influenza forecasters in the United States. In addition to maintaining the largest public repository of real-time indicators of COVID-19 activity, it has also been making foresasts of COVID-19 cases and deaths since March 2020. In this project, we design a customizable, interactive, parameterized report for evaluating and comparing performance of several COVID-19 forecasters for cases, deaths, and hospitalizations. Such a report helps provides Delphi insight into the performance of several forecasters over time periods, geographic locations using a choice of metrics. Our approach can be used to generate other informative reports in a production environment.
Measuring spatial-temporal change of physical conditions in neighborhoods with street view imagery
Neighborhood environmental characteristics play an essential role in shaping the health of individuals and communities, consequently contributing to inequality in the U.S. However, studies on neighborhoods have been constrained by limited data, limited methods, and extensive costs for capturing neighborhood environments characteristics at a large spatial-temporal scale. Partnering with Changing Cities Research Lab, we build a deep learning pipeline to systematically and automatically identify the physical conditions of neighborhood environments at a large scale, across multiple cities and over 10 years, using innovative street view images and crowd-sourcing data. This project will further help researchers to analyze how spatial-temporal changes of physical neighborhood conditions affect individual- and community- level of health.
Operationalizing Equity Tiebreaker in San Francisco Student School Assignment
The San Francisco Unified School District (SFUSD) has partnered with the SDS DSSG team to develop a policy recommendation for how students are assigned to public elementary schools in SFUSD. This zone-based assignment policy incorporates an equity tiebreaker priority to improve access to schools for historically underserved communities. In this project, the team identified appropriate geographic proxies for assigning equity tiebreakers and explored the effect of the equity tiebreaker on improving equity of access. This project helps to inform the implementation of the equity tiebreaker in the assignment policy in the school year 2023-24.
Sign up for DSSG announcements through the Stanford Data Science mailing list.
Are you interested in becoming a student fellow or mentor next summer? Add yourself to the mailing list and we’ll contact you when next summer’s applications for fellows and mentors are up in early spring. Summer 2022 will be open to non-Stanford affiliated students!
Do you have a social good project that you think DSSG could help with? If you’re interested in partnering with us, please add your name to this list, and we will notify you later this winter when the application for partnerships for next summer goes live.