Ning Yu
Los Angeles, California, United States
Summary
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RockstarNing Yu is a Lead Research Scientist with nine years of research and industry experience, currently heading video GenAI full-stack R&D at Netflix to bridge generative modeling and filmmaking workflows. He holds a joint Ph.D. from University of Maryland and MPI for Informatics and has driven multimodal and visual GenAI projects at Eyeline, Salesforce, NVIDIA, and Adobe. Ning’s publications span foundational and applied work—GAN fingerprints, controllable texture synthesis, multimodal agents, and video foundation models—frequently serving community roles as (Lead) Area Chair for top ML/CV conferences. His work has been recognized by industry fellowships and media coverage, and he combines deep academic rigor with product-minded engineering to push final-pixel and agentic modeling into production. Notably, he pursues research that centers attribution and robustness (e.g., GAN fingerprinting) alongside creative applications, making his portfolio uniquely relevant to both trust and storytelling in generative AI.
9 years of coding experience
Github Skills (13)
generative-model10
deepfake10
training-data10
tensorflow9
caffe9
fingerprinting9
pytorch9
diffusion-models7
multimodal5
go4
lmms2
text-generation2
agent1
Programming languages (1)
Github contributions (5)
ningyu1991/DefectDetection
Jan 2018 - Oct 2021
The official Caffe implementation for WACV'18 paper 'Learning to Detect Multiple Photographic Defects'
Contributions:34 commits, 37 pushes, 1 branch in 3 years 9 months
caffe
ningyu1991/ArtificialGANFingerprints
Nov 2020 - Oct 2021
The official PyTorch implementation for ICCV'21 Oral paper 'Artificial GAN Fingerprints: Rooting Deepfake Attribution in Training Data'
Contributions:49 commits, 22 pushes, 1 issue in 10 months
deepfakepytorchtraining-data
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