Fanjie Kong
Applied Scientist at 亚马逊网
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolFanjie Kong is an Applied Scientist with 8 years of experience bridging computer engineering research and product-focused machine learning at Amazon and AWS, currently working on auto-dubbing for Prime Video in Seattle. With a PhD from Duke, Fanjie specializes in computationally efficient and interpretable vision models, applying Multiple-Instance Learning and leveraging vision-language foundation models for open-world object detection. Their work blends state-of-the-art architectures like Vision Transformer and CLIP with rigorous attribution methods (Integrated Gradients, SHAP, DeepLIFT, LIME) and novel evaluation schemes, demonstrating a rare mix of model performance, interpretability, and causal evaluation. Comfortable moving ideas from research to production through internships and applied roles, Fanjie brings deep academic training and practical experience in multimodal systems to multimedia and video AI problems.
8 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Computer Engineering, Doctor of Philosophy - PhD, Computer Engineering at Duke UniversityBachelor's Degree, Biomedical/Medical Engineering, Bachelor's Degree, Biomedical/Medical Engineering at Northeastern University (CN)
Github Skills (23)
markdown10
jekyll10
representation-learning9
large-image9
torchvision9
jekyll-theme9
github-pages9
html9
classification8
contrastive-learning8
unsupervised-learning8
machine-learning5
pytorch5
deep-learning4
python3
Programming languages (4)
Github contributions (5)
timqqt/Synthinel
Jan 2020 - Mar 2022
Contributions:4 commits, 78 pushes, 1 branch in 2 years 2 months
timqqt/pytorch-zoom-in-network
Mar 2022 - Oct 2022
Source code for "Efficient Classification of Very Large Images with Tiny Objects"
Contributions:29 commits, 27 pushes, 1 branch in 7 months
classificationlarge-image
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