My work lies at the intersection of deep learning, computer vision, and robotics. More details can be found in my CV.
Work
Tech lead of the Perception team. Responsible for the tracking and motion prediction modules within our end-to-end driving model.
TLM of the Vehicle Perception team, leading a team of 10+ engineers.
❖ Foundation Sensor Model
Defined the roadmap and technical direction for Woven’s end-to-end perception system. Owned the development of core capabilities including 3D detection and tracking, multi-sensor fusion, and large-scale foundation training.
❖ ML Edge Compute
Led a cross-functional team to deploy and optimize ML models across multiple hardware platforms (Qualcomm, NVIDIA). Built the end-to-end deployment pipeline from the ground up, including model conversion, quantization, and on-device validation.
Lyft Level 5 was acquired by Woven by Toyota in July 2021.
High-fidelity 3D eye segmentation using implicit neural representations.
Lidar-based detection model for large vehicles.
Selected Publications
LCD: Learned Cross-domain Descriptors for 2D-3D Matching
Quang-Hieu Pham, Mikaela Angelina Uy, Binh-Son Hua, Duc Thanh Nguyen, Gemma Roig, and Sai-Kit Yeung
In AAAI, 2020.
A*3D: An Autonomous Driving Dataset in Challenging Environment
Quang-Hieu Pham*, Pierre Sevestre*, Ramanpreet Singh Pahwa, Huijing Zhan, Chun Ho Pang, Yuda Chen, Armin Mustafa, Vijay Chandrasekhar, and Jie Lin
In ICRA, 2020.
JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds
Quang-Hieu Pham, Duc Thanh Nguyen, Binh-Son Hua, Gemma Roig, and Sai-Kit Yeung
In CVPR, 2019.
Real-time Progressive 3D Semantic Segmentation for Indoor Scenes
Quang-Hieu Pham, Binh-Son Hua, Duc Thanh Nguyen, and Sai-Kit Yeung
In WACV, 2019.
SceneNN: A Scene Meshes Dataset with aNNotations
Binh-Son Hua, Quang-Hieu Pham, Minh-Khoi Tran, Duc Thanh Nguyen, Lap-Fai Yu, and Sai-Kit Yeung
In 3DV, 2016.