Data for Good

Service, outreach, and community-engaged data science

Beyond research, I am deeply committed to data science education and data for good outreach. The following are a few select initiatives that I am passionate about.

Statistics in the Community (STATCOM)

STATCOM is a volunteer student organization that provides pro bono statistical consulting services to non-profit and community organizations. This work spans projects from understanding community health perceptions after the Flint Water Crisis to supporting trans youth advocacy and improving access to fresh produce in food deserts. As president of STATCOM at the University of Michigan, I helped coordinate teams of student volunteers working on projects with mission-driven organizations. These collaborations often involved:

  • Designing and analyzing surveys to understand community needs
  • Building predictive and descriptive models to guide program decisions
  • Creating visualizations and tools that partners could use after our projects ended

This work benefits both community partners, who gain access to expertise and resources they might not otherwise have, and our students, who gain experience working with real data and collaborators posing meaningful, tangible questions that affect their local communities.



Example Collaboration: Starr Commonwealth

“Starr Commonwealth partnered with Statistics in the Community (STATCOM) at the University of Michigan for external validation of its program of work. Starr provides community-based programs and behavioral health services for children, youth, and families as well as professional learning for educators and clinicians in trauma-informed, resilience-focused care. Part of Starr’s mission is to increase accessibility to trauma-informed, resilience-focused, evidence-based intervention tools and programs.”


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MIDAS Student Leadership Team

The MIDAS Student Leadership Team (Michigan Institute for Data Science) brings together students from across campus who are interested in data science, outreach, and community-building. As part of this team, I:

  • Helped shape student-facing programming, including seminars, workshops, and networking events
  • Supported initiatives that connect students with real-world, socially impactful data projects
  • Advocated for inclusive, accessible training and mentorship pathways in data science

This work complements my STATCOM experience by extending data-for-good activities to a broader, cross-disciplinary community and by embedding data science education within a larger institutional ecosystem. As part of the student leadership team, I served on the Data for Good and Women+ Data Science committees.


Cancer AI Alliance (CAIA)

The Cancer AI Alliance is a landmark, multi-institutional initiative connecting Fred Hutch, Dana-Farber, Memorial Sloan Kettering, and Sidney Kimmel to enable secure, federated AI model development across more than one million patients. I work collaboratively with faculty and investigators while maintaining an independent research agenda focused on statistical frameworks for inter-institutional, AI-driven studies. I am currently working on a prioritized CAIA project with the Allen Institute for AI, applying AI to real-world NSCLC outcomes. My involvement centers on:

  • Developing and evaluating AI/ML models for precision oncology
  • Studying how AI-generated predictions can be used responsibly in downstream statistical inference
  • Building infrastructure and workflows so that models are transparent, reproducible, and aligned with real clinical needs

Within CAIA, I view data for good as encompassing not only community-facing outreach, but also responsible deployment of AI in high-stakes settings, ensuring that methods are rigorously validated, interpretable, and equitable.

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