Yuenan Hou
Research Postgraduate (RPg)
Hong Kong, China
Summary
🤩
Rockstar🎓
Top SchoolYuenan Hou is a 3rd-year Ph.D. candidate at MMLab, The Chinese University of Hong Kong, with nine years of experience bridging academic research and industry in computer vision. Supervised by Prof. Chen Change Loy and Prof. Xiaoou Tang, his work focuses on semantic segmentation, knowledge distillation, and reinforcement learning, with current projects on road marking segmentation and distillation for resource-constrained deployment. He has interned at SenseTime’s autonomous driving and 3D detection teams, where he led efforts on latency- and memory-aware pruning and proposed a group sparsity constraint tailored for FPGA channel requirements. Combining rigorous academic training with practical system-aware optimizations, he targets solutions that translate research gains into deployable models. Based in Hong Kong and affiliated with Shanghai AI Lab, he brings deep expertise in model compression and real-world vision pipelines that balance accuracy and hardware constraints.
9 years of coding experience
Bachelor's degree, Automation Engineer Technology/Technician, 4.72 / 5, Bachelor's degree, Automation Engineer Technology/Technician, 4.72 / 5 at Nanjing UniversityThe Chinese University of Hong Kong (CUHK)
Github Skills (102)
python10
vehicle-detection10
lua10
deep-learning10
self-attention10
model-compression10
neural-network10
tensorflow10
machine-learning10
convolutional-neural-networks9
kalman-filter9
ml9
pytorch9
deep-neural-networks9
data-science9
Programming languages (7)
Github contributions (5)
cardwing/cardwing.github.io
Oct 2018 - Feb 2025
Contributions:107 pushes, 1 branch in 6 years 5 months
cardwing/Codes-for-PVKD
May 2022 - Dec 2022
Point-to-Voxel Knowledge Distillation for LiDAR Semantic Segmentation (CVPR 2022)
Contributions:11 commits, 10 pushes, 1 branch in 6 months
cvpr2022lidar-segmentationnuscenespoint-cloud-segmentationpytorch
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