Many talks show how to make Python code faster. This one flips the script: what if we try to make our Python as slow as possible? By exploring deliberately inefficient programs — from infinite loops to Turing machines that halt only after an astronomically long time — we’ll discover surprising lessons about computation, large numbers, and the limits of programming languages. Inspired by new Turing machine results, this talk will connect Python experiments with deep questions in theoretical computer science.

This lighthearted educational talk explores the wild west of dataframes. We discuss where dataframes got their origin (it wasn't R), how dataframes have evolved over time, and why dataframe is such a confusing term (what even is a dataframe?). We will look at what makes dataframes special from both a theoretical computer science perspective (the math is brief, I promise!) and from a technology landscape perspective. This talk doesn't advocate for any specific tool or technology, but instead surveys the broad field of dataframes as a whole.