Contact

The best way to reach me is by email: kdreuther@ucsd.edu. A short note about what you’re working on and what you need is plenty.

Below are the kinds of conversations I’m most often asked about.

Workshops and seminars

I run workshops and invited seminars for departments, programs, teaching centers, and companies. Common topics: curricular design with AI, active learning, assessment design in the age of AI, and prompt engineering for educators. Formats range from a one-hour talk to a multi-day hands-on workshop.

AI collaborations on pedagogical projects

If you’re working on a teaching or learning project and need someone on the AI side — scoping the tool, designing the pedagogy around it, building a prototype, or running a study on how students actually use it — I’m interested. I’m especially keen on projects in biology, but I work across STEM and the humanities.

Help installing or adapting my web apps

My tools (Schema Study, AI Personas, the embeddable chatbot template) are designed to be set up without coding, but “no coding required” and “zero friction” aren’t the same thing. If you’re stuck on a Hugging Face fork, an API key, an LMS embed, or adapting a tool for your course, send me an email and I’ll help you get it running.

Joining the lab

I take on students for research credit and, when funding allows, through paid listings on the REAL portal and the UCSD Academic Internship Program.

I also have side projects that I’m actively looking for undergraduates to lead and push forward. Two current directions:

  • Machine learning and grading equity in the classroom. Extending a machine-learning approach to detecting and minimizing bias in classroom grading. See my SABER West poster, Machine Learning Inequity in the Classroom, for the starting point.
  • Human inability to spatially sample randomly. Designing an in-class active learning lesson that takes students through a complete investigative cycle demonstrating why science has to work hard to minimize sampling bias — using the well-documented human failure to sample space randomly as the case study.

If either direction interests you, email me with a short note about your background and what draws you to the project.

  • Interested in writing for the blog? Send a short writing sample you’re proud of.
  • Interested in building learning tools? Most of my current work is in Python with a range of LLMs, and most of my web apps are in Streamlit — but I use whatever the project calls for, including JavaScript or R Shiny. What I care about isn’t the stack; it’s whether you can work fluently across tools. You should have solid AI literacy and be comfortable designing simple web apps and picking up new frameworks on your own. A good proof point: you’ve already built a small web app that’s useful to you, figured out how to test it, and pushed it live using some combination of AI assistance, your own coding, and open-source tools.

Mailing address

Keefe Reuther UC San Diego · School of Biological Sciences 8085 HSS Building · 9500 Gilman Dr. · Mail Code 0101 La Jolla, CA 92093