Scholar
Tao Yu
Google Scholar ID: lbi95bUAAAAJ
Machine Learning Scientist, AWS AI
Citations & Impact
Citations
7,067
H-index
11
i10-index
11
Publications
20
Co-authors
11
list available
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- No specific details provided about academic achievements.
Research Experience
- Currently an Applied Scientist at the AWS Neuron Science team supporting AWS Trainium/Inferentia chips. Previously worked on machine learning privacy projects with Vitaly Shmatikov.
Education
- Ph.D. in Computer Science from Cornell University, advised by Chris De Sa; Bachelor's degree in Mathematics (ZhiYuan Honors) from Shanghai Jiao Tong University, advised by John E. Hopcroft and Huan Long.
Background
- Interested in efficient machine learning systems, focusing on designing data-aware representations, optimizing computational efficiency, and advancing system performance to enable scalable learning. Topics of interest include low-precision training, inference, and learning with non-Euclidean representations. Also interested in private and robust machine learning algorithms.
Miscellany
- Recently passionate about algorithm–hardware co-design, aiming to understand the limitations of hardware & software, leverage their features, and design supports for efficient and reliable training and inference.
