Jing Pu

Jing Pu is a Staff Software Engineer at Waymo, specializing in machine learning infrastructure. With a PhD in Electrical and Electronics Engineering from Stanford University, Jing's research focused on mapping image processing pipelines onto CPU/FPGA systems using the open-source language Halide. They have previously worked at Google, leading the EdgeTPU and Tensor SoC ML Accelerator Compiler projects, as well as having interned at Intel China Research Center and Samsung Electronics. Jing has also contributed to academia as a Teaching Assistant at Stanford, designing a course project module on hardware generator concepts.