Xiao-Yu Xiang is a Senior Research Scientist at Meta Reality Labs with 11 years of experience bridging physics-driven engineering and cutting-edge computer vision and machine learning. Trained in engineering physics at Tsinghua and pursuing a PhD at Purdue, she has a strong experimental background from fiber laser research and particle-detector testing, which informs her empirical approach to ML problems. At Meta she progressed from research intern to senior scientist after internships at Facebook, ByteDance and HP where she worked on real-world image restoration, temporal smoothing for video landmarks, and face-set recognition. An active open-source contributor and ML engineer, she implemented and evaluated a one-stage space-time video super-resolution model from the CVPR 2020 literature, reflecting a deep engagement with video enhancement research. Outside the lab she’s an indie app developer with five apps on sale, demonstrating a practical focus on shipping products that translate research into user-facing tools.
Fast and Accurate One-Stage Space-Time Video Super-Resolution (accepted in CVPR 2020)
Role in this project:
ML Engineer
Contributions:1 review, 17 commits, 5 PRs in 2 months
Contributions summary:Xiaoyu's commits focused on implementing and testing a video super-resolution model. The code modifications included the addition of model files, test scripts, and training-related Python files. These changes suggest involvement in developing and evaluating a deep-learning-based approach to enhance video quality. Further contributions involved incorporating utility functions and data-handling scripts.
Contributions:21 commits, 18 pushes, 1 branch in 1 year 2 months
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