AI tools for research are advancing at a pace that often outstrips traditional academic training. These tools are powerful, but using them effectively to produce high quality research is a skill in itself. So how do we use AI to move faster and accelerate biological discovery without sacrificing scientific rigor and our sense of engagement with our work?

We hope to build a community dedicated to keeping up with new tools, sharing ai-augmented research workflows what work well, and staying human in an AI world.

We are launching the Biomedical Gen AI Learning Community!

Open to: Anyone in the UM bioinformatics and biomedical community - researchers, students, and staff.

How The Learning Community Works:
Our biweekly 60-minute sessions are broken into three high-impact segments:

The Spotlight (20 mins): A volunteer demonstrates a specific workflow they’ve integrated into their research. (Examples: Hypothesis generation, AI agent creation, GitHub management, or Literature synthesis).

Foundational Knowledge (20 mins): A focused tutorial on the skills needed to direct AI tools and critically evaluate outputs. (Example: Key safety considerations when deploying agents or best practices for software management).

The Human Side (10 mins): An open, facilitated discussion on navigating our changing relationship with work, learning, and intellectual identity in the age of AI. (Example: The Engagement Gap: Talking about the 'boredom' of automation—how to stay excited about a project when the AI is doing the heavy lifting?)

The Biomedical Gen AI Learning Community is sponsored by the Center for Computational Medicine and Bioinformatics (CCMB)