Yuchuan Gou

Machine Learning Engineer

Machine Learning Engineer at Zoox, specializing in AI inference for autonomous driving systems. With 7 years of experience in ML infrastructure, ML deployment, and MLOps. Focusing on on-vehicle AI Inference stack, and scalable AI Infra on cloud. His research spans generative models, super-resolution, with publications in CVPR workshops and SIGGRAPH. He is a CVPR challenge winner, holds 9 patents, and has gained over 2000 GitHub stars.

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Presentation

AI Model Deployment and Optimization in Autonomous Driving

This technical session offers a deep dive into the deployment and optimization of AI models powering autonomous driving systems. It walks through some industry-standard workflows, from model development to real-time deployment in embedded automotive platforms. The presentation will cover critical topics such as inference acceleration, quantization, pruning, and runtime optimization on Autonomous Driving hardware. Attendees will gain insights through practical examples, toolchains, and performance benchmarks, highlighting best practices and common pitfalls in deploying AI on autonomous vehicles.