Zhenli Zhang
About Zhenli Zhang
Zhenli Zhang is a Machine Learning Engineer with experience in conditional behavior prediction and sensor fusion techniques. He has worked at Nuro since 2021 and previously interned at MEGVII and Waymo, while also holding degrees from Fudan University and Carnegie Mellon University.
Work at Nuro
Zhenli Zhang has been employed at Nuro as a Machine Learning Engineer since 2021. In this role, Zhang focuses on developing advanced machine learning models, particularly in the area of conditional behavior prediction. This work contributes to Nuro's mission of creating autonomous delivery vehicles that can navigate complex environments.
Education and Expertise
Zhenli Zhang holds a Bachelor of Science in Computer Science from Fudan University, where studies spanned from 2014 to 2019. Zhang furthered education by earning a Master of Science in Computer Vision from Carnegie Mellon University in 2020. Additionally, Zhang participated as an exchange student at UC Irvine in 2016, gaining exposure to diverse academic environments.
Background
Zhenli Zhang began a career in machine learning with an internship at MEGVII in Beijing, China, from 2017 to 2018. During this time, Zhang implemented sensor fusion techniques to improve object detection and semantic segmentation. Following this, Zhang interned at Waymo in 2020, where the focus was on research for three months in Mountain View, California.
Achievements in Machine Learning
Zhenli Zhang has made significant contributions to machine learning projects, particularly in the development of a diffusion model for behavior modeling. This model is utilized for smart agents in simulation, onboard prediction, and onboard planning. Zhang has also employed reinforcement learning techniques for various planning applications, enhancing the capabilities of machine learning systems.