junjiek
Summary
👤
SeniorJunjie Ke is a Staff Software Engineer at Google DeepMind with 11 years of experience specializing in computer vision, generative AI, and multimodal quality assessment. He previously led multimodal quality efforts at Google Research, contributing practical model improvements such as preprocessing and positional embedding code for the widely referenced google-research MUSIQ project. A Stanford CS master’s graduate and former TA for flagship NLP and iOS courses, he blends rigorous academic grounding with production-focused engineering. Based in Palo Alto, he focuses on raising the fidelity of generated media across modalities, combining research sensibilities with hands-on model and systems development.
11 years of coding experience
Github Skills (5)
computer-vision10
machine-learning10
tensorflow10
python10
image-processing10
Programming languages (4)
Github contributions (5)
google-research/google-research
Aug 2021 - Jun 2022
Google Research
Role in this project:
ML Engineer
ML EngineerContributions:5 commits, 7 comments in 10 months
Contributions summary:junjiek contributed code related to the MUSIQ model, specifically focusing on preprocessing operations for image patches within the `google-research/google-research` repository, which is focused on AI and machine learning research. The changes involve defining functions for resizing images, extracting patches, and generating positional embeddings. Furthermore, the user made corrections to VILA and the integration of tfhub and musiq, indicating ongoing model development and refinement.
googlemachine-learningai
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