AI for Social Impact in Agriculture
With funding from the NSF & USDA and as part of the AI Institute for Resilient Agriculture (AIIRA), this workforce development and applied data science program supports interdisciplinary undergraduate research teams to take on AI/ML projects as part of the Iowa State University DSPG summer training program.
Data Science for the Public Good Summer Program
With USDA and Gates Foundation funding support
DSPG 2020 is now closed. See here to learn more about the interns, fellows, and projects of the 2020 cohort.
To apply to DSPG 2021, see here.
A recent news article about DSPG.
Program Overview
The Data Science for the Public Good (DSPG) Young Scholars program is an immersive summer program held at the Social Analytics Laboratory in the Department of Sociology at Iowa State University. The program engages students from across Iowa to work together on projects that address local and state government challenges around critical social issues relevant in the world today. DSPG resident scholars conduct research at the intersection of statistics, computation, and the social sciences to determine how information generated within every community can be leveraged to improve quality of life and inform public policy.
The summer 2020 program runs for 10 weeks (May 18 - July 24). Working in teams, fellows and interns collaborate with project stakeholders and research faculty across the Iowa State University data science community. Research teams combine disciplines including statistics, data science, and the social and behavioral sciences to address complex problems proposed by local, state, and non-profit agencies. Students work on multiple projects of their choice and interact with different scholars, faculty, and sponsors over the course of the training program.
To learn about the kinds of projects scholars can expect to work on during the 2020 program, see DSPG projects and young scholars from the 2019 program at the University of Virginia.
Fellows and interns are selected through a competitive state-wide search. Graduate fellows should possess strong quantitative, statistical, computational and programming skills. They lead, support, and guide undergraduate students together with ISU faculty and research associates. Undergraduate students acquire experience in programming and statistical analysis through a combination of both formal training and practical application to the real-world problems of our community and agency partners.
Program Highlights
The DSPG program equips a new generation of emerging scientists with the skills needed to inform intelligent governmental policy and decision-making.
- Horizontally and vertically integrated team research with dedicated graduate students and faculty in collaboration with sponsors from local, state, and\or federal agencies
- Expert training in foundational tools for quantitative computing and data visualization, including R, GIS, Tableau, and databases
- Professional training through workshops, seminars, and career talks
- Individualized mentors working closely with students
- Technical report and publication opportunities
- Opportunity to interact with decision-makers in local communities, non-profits, and state government agencies
Midwest Big Data Hub Summer School
I have been an instructor in the NSF funded MBDH Data Science bootcamp, where I have introduced students to computational propaganda tools, methods, and theories, and where I have introduced students to health analytics using Tableau.
Computational Propaganda (2018)
Computational Propaganda (2019)
Visualizing Health Data with Tableau (2020)
DS 401: Data Science Internship
Through the Public Science Collaborative, I supervise Data Science student interns taking credits in Data Science 401. Interns use their data science skills to develop data tools such as dashboards, data infrastructure, and custom analytics that help to solve pressing real-world problems in the social sector. Public Science Collaborative interns get to work along side professional data science consultants and policy analysts, practice the profession, improve your coding, expand you data visualization skills, and work in a collaborative, team-based environment.