Joe Cheng
Joe Cheng is CTO and first employee at Posit (formerly known as RStudio) and the creator of Shiny, a reactive web framework for creating data and AI applications using Python or R. He has been writing and maintaining open source software at the intersection of data analysis and the web for over 15 years.
Sessions
LLMs are powerful, flexible, easy-to-use... and often wrong. This is a dangerous combination, especially for data analysis and scientific research, where correctness and reproducibility are core requirements. Fortunately, it turns out that by carefully applying LLMs to narrower use cases, we can turn them into surprisingly reliable assistants that accelerate and enhance, rather than undermine, scientific work.
This is not just theory—I’ll showcase working examples of seamlessly integrating LLMs into analytic workflows, helping data scientists build interactive, intelligent applications without needing to be web developers. You’ll see firsthand how keeping LLMs focused lets us leverage their "intelligence" in a way that’s practical, rigorous, and reproducible.