Akshay Agrawal
Akshay Agrawal is currently building marimo, a new kind of reactive notebook for Python that is reproducible, git-friendly (stored as Python files), executable as a script, and deployable as an app.
He is both a researcher, focusing on machine learning and optimization, and an engineer, having contributed to several open source projects, including TensorFlow during his time at Google, and CVXPY, of which he is a maintainer. He holds a PhD from Stanford University, where he was advised by Stephen Boyd, as well as a BS and MS in computer science from Stanford.
Sessions
Python notebooks are a workhorse of scientific computing. But traditional notebooks have problems — they suffer from a reproducibility crisis; they are difficult to use with interactive widgets; their file format does not play well with Git; and they aren't reusable like regular Python scripts or modules.
This talk presents a marimo, an open-source reactive Python notebook that addresses these concerns by modeling notebooks as dataflow graphs and storing them as Python files. We discuss design decisions and their tradeoffs, and show how these decisions make marimo notebooks reproducible in execution and packaging, Git-friendly, executable as scripts, and shareable as apps.