<> AI Research @ UVA · Faculty AI Upskilling Workshop
Designing an AI-Powered Research Pipeline
You didn’t learn Excel or R by collaborating with them — you dictated every step. Generative AI rewards the opposite instinct, and that’s the under-recognized sticking point: you don’t learn to use AI, you learn to interact with it.
> For faculty, PhD students & research staff in any discipline — no coding or prior AI experience required.
This hands-on workshop helps established researchers make that shift. A design-sprint front end helps you define AI-era research questions you might not have thought to ask — or even thought possible.
Then we get concrete: you’ll build a context library — your own expertise, written up so an AI can work from it — explore your research space, including new data sources and tools that generative AI makes feasible, build interactive prototypes to see where those trajectories might lead, and leave with a personal roadmap for your own AI-powered research pipeline: your own way of working with AI, not a piece of software you have to maintain.
Who Should Take This
Established researchers with deep domain expertise — faculty, PhD students, and research staff in any discipline — who don’t (yet) think of themselves as AI researchers. No coding or prior AI experience required — most people in the room will be trying this for the first time, and that’s the point. Bring a laptop and one research domain you know cold.
Leave With
- AI-era research questions from your own domain — including ones you’d previously have ruled out as infeasible
- A starter context library — your expertise and question, structured so an AI system can actually work with it
- Interactive prototypes exploring where those research trajectories might lead
- A personal roadmap for your own AI-powered research pipeline — and a clear sense of where traditional methods re-enter
AI doesn’t replace your expertise — it makes it buildable.
The Two Hours
Logistics
Before you come: create a Claude account (a paid Claude Pro account is ideal). You’ll never need to share sensitive or unpublished work — we practice on public or synthetic examples, and the same moves carry directly into UVA’s licensed tools (Microsoft Copilot, Google Gemini / NotebookLM) when you turn to your real institutional work.
How This Is Grounded
This workshop is designed as a human on-ramp to the goals of AI Research @ UVA — to “cultivate the next generation of AI researchers and practitioners” and move the University from “isolated pockets of excellence to a unified Networked University.”
The method behind it is a design sprint: define the right question, ground the AI in your expertise, prototype fast. It’s the same approach that powered the Health Design Sprint, where eight medical students with no coding background shipped working clinical tools in ten days — built on the UVA Medical Design Program, which has trained 200+ students in human-centered design since 2017.
Health is where the method was proven, but the way of working — and thinking — transfers to any discipline: a historian structuring an archive, a nurse redesigning a care workflow, an economist exploring a new dataset.
An Associate Professor of Emergency Medicine and Public Health Sciences at the UVA School of Medicine, and Director of the UVA Medical Design Program — which has taught human-centered design to 200+ clinicians since 2017.
His work focuses on putting design thinking — and now generative AI — directly in the hands of domain experts, so the people closest to a problem can build for it.
Free · In-person · Refreshments provided · Seats limited to 20.
A new podcast episode with Matt Trowbridge releases alongside this workshop.
Questions? Ryan Wright · rtw2n@virginia.edu