Xinshuo Weng is a Senior Research Scientist at NVIDIA with a decade of experience bridging 3D computer vision, autonomous driving, and generative models. A CMU Robotics PhD alum and Qualcomm Fellowship recipient, he has advanced end-to-end AV systems, traffic simulation, online mapping, and LLM/VLM integration for vehicles. His work spans research and engineering—contributions include practical fixes and evaluation improvements to the widely used AB3DMOT 3D multi-object tracking codebase. Prior roles at Oculus and Meta focused on facial, body and hand pose estimation, reflecting a strong track record in human-centric perception as well as vehicle-centric autonomy. Based in Toronto, he combines deep academic training with product-facing research that ships in large-scale systems.
10 years of coding experience
3 years of employment as a software developer
B.S. in Electrical Engineering, B.S. in Electrical Engineering at Wuhan University
Ph.D. in Robotics Computer Vision and Machine Learning, Ph.D. in Robotics Computer Vision and Machine Learning at Carnegie Mellon University School of Computer Science
(IROS 2020, ECCVW 2020) Official Python Implementation for "3D Multi-Object Tracking: A Baseline and New Evaluation Metrics"
Role in this project:
ML Engineer
Contributions:216 commits, 30 PRs, 196 pushes in 2 years 9 months
Contributions summary:Xinshuo primarily contributed to the `evaluation/evaluate_kitti3dmot.py` file, indicating a focus on evaluating 3D multi-object tracking performance. Their commits included modifications to the evaluation metrics, addition of results for pedestrian and cyclist classes, and support for Python 3.5 compatibility. Furthermore, they fixed orientation correction bugs within the `main.py` file and updated the example usage within the `trk_conf_threshold.py` file.
Contributions:15 commits, 14 pushes, 1 branch in 11 months
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Xinshuo Weng - Senior Research Scientist at NVIDIA