Gordon Qian
AIGC Intern at Snap Inc.
Sunnyvale, California, United States
Summary
🤩
Rockstar🎓
Top SchoolGordon Qian is a research-oriented machine learning scientist with seven years of experience building generative and 3D AIGC systems, currently interning at Snap in Sunnyvale. He holds a PhD from KAUST and a strong engineering foundation from Xi'an Jiaotong, and has contributed to research and production projects across Meta, Microsoft, SenseTime, and MEGVII. His work spans point-cloud foundation models (PointNeXt), efficient video processing (GTMNet), neural architecture search, and end-to-end RAW image pipelines, reflecting a blend of academic rigor and applied engineering. An active open-source contributor, he has improved training and evaluation pipelines for the well-known DeepGCNs PyTorch repo, focusing on robustness and model metrics. Colleagues describe him as someone who moves seamlessly between research prototypes and production-ready code, often spotting subtle data-processing issues that materially improve results. Based in Silicon Valley, he’s focused on pushing generative models toward practical 3D and video applications.
7 years of coding experience
1 year of employment as a software developer
Bachelor of Engineering - BE, Mechanical Engineering, 3.9/4.3, Bachelor of Engineering - BE, Mechanical Engineering, 3.9/4.3 at Xi'an Jiaotong UniversityDoctorate Degree, Computer Science, 3.9/4.0, Doctorate Degree, Computer Science, 3.9/4.0 at King Abdullah University of Science and TechnologyHong Kong University of Science and Technology (HKUST)
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (9)
computer-vision10
pytorch10
graph-neural-network10
python10
machine-learning9
data-mining9
modeling8
point-cloud8
trainings8
Programming languages (6)
Github contributions (5)
lightaime/deep_gcns_torch
Aug 2019 - Feb 2022
Pytorch Repo for DeepGCNs (ICCV'2019 Oral, TPAMI'2021), DeeperGCN (arXiv'2020) and GNN1000(ICML'2021): https://www.deepgcns.org
Role in this project:
ML Engineer
ML EngineerContributions:44 commits, 89 pushes, 33 comments in 2 years 6 months
Contributions summary:Gordon primarily contributed to the project by modifying and updating code related to training and evaluation scripts. The modifications involved changes to the training process, including disabling data augmentation in the part segmentation example and modifying the configuration files for training. Additionally, the user worked on model adjustments by detaching tensors and fixing shape IoU calculations. These changes suggest a focus on improving model performance and streamlining the training pipeline within the DeepGCNs framework.
cheminformaticspytorchsocial-networkarxiviccv
guochengqian/KAUSTian_Handbook_CN
Jan 2021 - Jan 2023
KAUST Handbook (in Chinese)
Contributions:6 reviews, 82 commits, 40 PRs in 1 year 11 months
chinesehandbook
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