Depu Meng
Research Engineer at Applied Intuition
Mountain View, California, United States
Summary
👤
Senior🎓
Top SchoolDepu Meng is a Research Engineer at Applied Intuition with nine years of experience building ML-driven perception and autonomy systems. He holds a PhD in Control Science and Engineering from USTC and has transitioned from academic research to industry, including postdoctoral work at the University of Michigan that helped his team win USDOT intersection safety challenges. His hands-on background spans lidar-based 3D detection, motion prediction, sensor simulation, and multimodal foundation models from roles at DiDi, Meituan, and Microsoft Research Asia. Depu combines deep research rigor with practical system-building for production autonomy stacks, moving seamlessly between model development and simulation environments. Based in Mountain View, he brings a track record of translating novel algorithms into deployable components for safety-critical driving systems. An understated strength is his consistent involvement in both foundational vision tasks and end-to-end autonomous pipelines, enabling cross-cutting solutions.
9 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Control Science and Engineering, Doctor of Philosophy - PhD, Control Science and Engineering at University of Science and Technology of China
Chinese, English
Github Skills (53)
transformers10
representation-learning10
pytorch10
high-resolution-net10
high-resolution10
language-model10
python10
pose10
machine-learning10
3d-object-detection10
seq2seq10
flax10
human-pose-estimation10
deep-learning10
tensorflow10
Programming languages (6)
Github contributions (5)
DeppMeng/HRNet-Semantic-Segmentation
Jul 2019 - Aug 2019
High-resolution representation learning (HRNets) for Semantic Segmentation
Contributions:230 pushes, 2 branches in 27 days
pytorchrepresentationsemantic-segmentationdeep-learningrepresentation-learning
michigan-traffic-lab/Ann-Arbor-Intersection-Trajectory-Data
Nov 2022 - Jan 2023
The dataset contains the vehicle trajectory data perceived by the roadside perception system deployed at the two-lane roundabout at the intersection of State St. and W. Ellsworth Rd. in Ann Arbor, Michigan.
Contributions:1 release, 18 commits, 1 PR in 1 month
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