Chenggang Liu

About

A curious learner and a passionate explorer in the fields of AI, robotics, and automation

2025 – Present

Motional AD

Working on ML-based trajectory generation for next-gen self-driving systems.

2023 – 2025

Meta Reality Lab Research

With the rise of GenAI, took a brief detour from motion intelligence to work on photorealistic Codec Avatars.

2021 – 2023

Aurora Innovation

Worked on a parametric trajectory sampler for L4 self-driving cars. The challenge in sample efficiency led me to explore ML approaches for trajectory generation.

2015 – 2021

Uber ATG

Worked on trajectory generation, solving three major challenges: optimization runtime performance; behavior formulation and tuning; and cost function learning.

2013 – 2015

Robotics Institute — Carnegie Mellon University

Worked on optimization-based motion planning and control for humanoid robots. Participated in the DARPA Robotics Challenge with Team WPI-CMU, leading the egress task. The team completed the task in under four minutes with a 100% success rate and placed 7th in the DRC final.

2008 – 2010

Robotics Institute — Carnegie Mellon University

Pioneered the use of an optimal trajectory library for robot planning and control. The trajectory optimization method I used later became one of the most efficient trajectory generation methods for self-driving cars.

Earlier

S3 Graphics

Worked on GPU logic design, which sparked my interest in harnessing computational power to drive advanced AI.