Partner Projects

LUCID is a project-focused cross-disciplinary graduate training program working on problems at the intersection of machine learning, human cognition, and education. The program seeks to prepare graduate students for both academic and non-academic career paths.

The educational intent of the potential partnership is to broaden understanding of how problems at the intersection of machine learning and human behavior are generated, used, applied or 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.

Through discussions with potential partner organizations, we realize that there are more problems than students. 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.

LUCID is currently a small group, but we are looking at the potential to grow. Understanding partners, projects and potential funding could assist with these decisions.

We are using this project board as a way for qualified students to become aware of problems and potential projects and for partner organizations to be able to highlight their research questions.

If you have a project to add to the board fill out: Partner Organization Projects

 

Current Available Projects for Students:

Nils Ringe, Department of Political Science, UW-Madison

Looking for a collaborator with the skills to empirically test propositions using computational science or machine learning tools and be a co-author in a political science journal. For more details: Ringe

ShoU

ShoU combines intelligent health monitoring tools with virtual access to healthcare providers. The platform enables users to track all relevant nutrition, exercise, and biometric data, while the provider network ensures accessible and affordable care. For more project details: ShoU