07-28, 14:00–17:30 (UTC), Green Track
Often, new comers to Julia face one of two issues: (1) write a quick Julia implementation that turns out slower than expected, and (2) find it hard to bridge existing codes in another programming language to Julia. In this workshop, I will show Julia tools and "aha-moments" that will allow your Julia code to be much faster, and walk through examples of wrapping Python, and C codes into Julia.
Join via Zoom: link in email from Eventbrite. Backup Youtube link: https://youtu.be/S5R8zXJOsUQ
Huda Nassar is a postdoctoral fellow at Stanford University specializing in computational immunology. Her work is currently focused on early disease prediction and specifically building low-rank models for these problems. She is an enthusiastic Julia user and has built the MatrixNetworks.jl package which is a graph algorithms package that treats graphs as matrices and utilizes linear algebra concepts to solve many standard graph problems.