OGPS Research in Motion: Project Management for Biomedical Scientists

Research rarely moves in a straight line. Experiments change, priorities compete, collaborators have different timelines, and unexpected results can reshape the plan entirely. Yet researchers are still responsible for keeping complex projects moving forward.

Research in Motion is a two-part professional development series designed to help graduate students and postdoctoral fellows apply practical project-management approaches to the realities of biomedical research. Participants will explore strategies for planning and prioritizing work, coordinating projects, communicating progress, adapting when plans change, and using emerging technologies responsibly.

The series connects day-to-day research challenges with transferable professional competencies—including project management, communication, collaboration, strategic planning, documentation, and professional judgment—that are valuable across careers in academia, industry, government, and other sectors.

Participants may attend either session independently or attend both to build a broader toolkit for managing research projects effectively.

If you have any questions, please reach out Dr. Ioannis Chremos (ichremos@umich.edu)



Leveraging AI for Research Project Management

-
VIRTUAL
Livestream Available (Visible After Registration)
Dr. Shayla Vradenburgh

Generative AI can help researchers plan, organize, communicate, and document their work—but using AI effectively requires more than knowing how to write a prompt. Researchers also need to determine where AI adds value, where human judgment remains essential, and what information is appropriate to share with different AI systems.

In this practical workshop, Dr. Shayla Vradenburgh will explore how AI tools and project-management principles intersect in biomedical research. Participants will examine ways AI can support common project-management tasks such as breaking down complex projects, developing timelines and action plans, preparing meeting agendas and follow-up documentation, communicating project status, identifying potential risks or gaps, and maintaining momentum across multiple priorities.

The session will also address responsible AI use in research environments, including the importance of verifying AI-generated output, protecting sensitive information, documenting appropriate uses, and recognizing tasks for which AI is not an appropriate substitute for researcher expertise or professional judgment.

Participants will leave with practical approaches they can adapt to their own research workflows and a framework for deciding when—and when not—to use AI as a project-management tool.

By the end of this session, participants will be able to:

  • Identify research project-management tasks for which generative AI may be useful.
  • Use AI to support planning, prioritization, communication, and documentation.
  • Develop prompts that provide sufficient context, constraints, and desired outputs for project-management tasks.
  • Evaluate AI-generated outputs rather than treating them as authoritative.
  • Recognize privacy, security, research-integrity, and other considerations when using AI in research workflows.
  • Identify opportunities to integrate AI selectively and responsibly into their existing project-management practices.
For questions or contact information click here