07-10, 09:15–10:00 (US/Pacific), Ballroom
There are many programming languages that we might choose for scientific computing, and we each bring a complex set of preferences and experiences to such a decision. There are significant barriers to learning about other programming languages outside our comfort zone, and seeing another person or community make a different choice can be baffling. In this talk, hear about the costs that arise from exploring or using multiple programming languages, what we can gain by being open to different languages, and how curiosity and interest in other programming languages supports sharing across communities. We’ll explore these three points with practical examples from software built for flexible storage and model deployment, as well as a brand new project for scientific computing.
Julia Silge is a data scientist and engineering manager at Posit PBC, where she leads a team of developers building fluent, cohesive open source software for data science in Python and R. She is a tool builder, author, international keynote speaker, and real-world data science practitioner. She holds a PhD in astrophysics and serves on the technical advisory committee of the US Bureau of Labor Statistics. You can find her online at her blog and YouTube.