Interested in the kinds of capstone projects students work on?
Alumni Drew Beatty shares her role in the capstone project in collaboration with Healthy Minds Innovation:
Interested in Collaborating with us?
We are looking for interested potential collaborators with a data science challenge (e.g. more data than time to analyze, data pipeline challenges from raw data to end-user visualizations, database implementation issues, ideas for recommendations/predictions, etc.) for a team of our students to tackle during their fall semester capstone project.
Through discussions with potential partner organizations, we realize that there are more problems than students. At this time, we are hoping to hear from as many potential collaborators so that we can find the best fit project for our student teams.
Many partner organizations have data and research questions, finding ways to collaborate with university research groups can be tricky. Often deciding on the scope, and finding common language for a project becomes a project itself. We recommend proposing something small, with the potential to scale if the collaboration is successful.
Understanding partners, projects and potential funding could assist with these decisions.
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Timeline:
Late Spring: Compile list of potential collaborators
Late May: Match student teams with projects and solidify data use agreements
June-August: Students spend 15 hours/week learning the skills needed to complete the deliverables for the fall semester. It is useful if they get access to real data at this point so they can spend time cleaning, learning, getting comfortable with analyzing and exploring insights.
End of Summer: Students create a statement of purpose for the fall semester capstone project and meet with the sponsor/collaborator to present what they have learned and a couple potential directions for what they could deliver.
Fall Semester: The sponsor can meet weekly, biweekly, or monthly with the student team based on interest and availability.
Mid-December: Students give a final presentation, share deliverables and documentation of insights during their graduation reception.
FAQ:
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How long would the commitment be for the project sponsor?
Students can start working on the project in the spring semester during their 10-week project, or in June when their capstone project begins.
Our students graduate in December and at that time, submit their final presentation, deliverables and documentation to the project sponsor.
The minimum commitment during the project is to iron out details for data use agreements (if necessary from your organization’s perspective), have someone meet with students to share your data and explain your data structure and project goals, attend a meeting in early fall to discuss deliverables and attend a meeting in December for students to transfer deliverables and share insights.
If interested, a member of your organization can meet weekly, biweekly, or monthly with the student team to discuss progress of the project.
Is there mentoring support for the students?
Yes! Student teams meet weekly with their PhD mentors to discuss any challenges they are facing and present what they have been working on. If several groups have similar training needs, we also bring in experts to our weekly capstone meetings to train them on topics like data visualization packages, high throughput computing etc. They also meet with faculty sponsors biweekly or monthly depending on need.
What relationship is there between DSHB program and the sponsor organization?
That is all up for discussion, the most pressing concerns are typically regarding data use agreements, nondisclosure agreements, external communication about the project, and monetary exchange.
We have sample data use agreements and nondisclosure agreements that have been developed in collaboration with our UW Research, Compliance and Sponsors team that can act as a starting point for our discussions.
We ask for permission to be able to share the nature of the project on our website for prospective students, and our communication team would get your okay before sharing any news about the project.
Regarding funding, we would like to move into a funding model at some point, or donation to the program so that we can fund our fearless PhD student mentors, but at this point we need more evidence of success before we make an ask!
What is AI & Society?
AI & Society is a cross-disciplinary community working on problems at the intersection of machine learning and human behavior.
Data Science in Human Behavior is part of the AI & Society community of graduate students, university staff and faculty as well as collaborators.
What is the educational intent of the capstone project?
One of the main goals for the capstone project is to broaden understanding of real-world data science challenges and how these problems are generated, used, applied and communicated outside of academia. This experience is also meant to introduce diversity of career pathways for scientists with advanced training as well as the professional culture of workplaces and organizations.
This experience should act as a springboard with transferable skills for the students’ career.