Yi Yang - Research Scientist at DeepMind

Yi Yang

Research Scientist at DeepMind

London, England, United Kingdom

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Summary

🤩

Rockstar

🎓

Top School

Yi Yang is a research scientist at DeepMind with 11 years of experience specializing in AI, machine learning, deep learning, and computer vision. He holds a PhD in Computer Science from UC Irvine and brings a track record of research-to-engineering impact from roles at Baidu USA and internships at Google and Microsoft. At DeepMind he contributes to cutting-edge vision research and has hands-on experience improving data pipelines for high-profile projects like TapNet’s Tracking Any Point, including Kinetics dataset integration and visualization. Comfortable moving between prototype research and production-ready engineering, he combines rigorous academic training with practical system-building in large-scale ML environments. Based in London, he blends classical robotics/mechatronics foundations with modern deep learning research, making him adept at bridging physical intuition and data-driven models.

11 years of coding experience

5 years of employment as a software developer

Hong Kong University of Science and Technology (HKUST)

Bachelor's Degree Mechatronics Robotics and Automation Engineering, Bachelor's Degree Mechatronics Robotics and Automation Engineering at Tsinghua University

University of California, Irvine

Chinese, English

Github Skills (6)

data-loading10

computer-vision10

deep-learning10

python10

numpy10

tensorflow3

Programming languages (3)

C++Jupyter NotebookPython

Github contributions (5)

google-deepmind/tapnet

Oct 2022 - Feb 2023

Tracking Any Point (TAP)

Role in this project:

ML Engineer

Contributions:32 commits, 5 PRs, 75 pushes in 4 months

Contributions summary:Yi's commits primarily involve modifications to the TapNet codebase, focusing on data loading and dataset integration for the Kinetics dataset. The user added a third-party data loader, updated the generate_tapvid.py script, and directly visualized the Kinetics dataset from a CSV file. These changes suggest a focus on expanding the dataset capabilities and potentially improving the data handling pipeline for the point-tracking model.

benchmarkcomputer-visiondeep-learningpoint-trackingrobotics

yangyi02/my-scripts

Mar 2016 - Nov 2017

Contributions:123 pushes, 1 branch in 1 year 8 months

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