He Kaiming
Kaiming He is a Chinese computer scientist who serves as an associate professor in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology and works part-time as a Distinguished Scientist at Google DeepMind. He is best known as one of the creators of the residual neural network (ResNet) architecture, and his 2016 paper Deep Residual Learning for Image Recognition became one of the most highly cited research papers in the field. He previously worked at Microsoft Research Asia and Facebook Artificial Intelligence Research. His research focuses on computer vision and deep learning.
“Even in the ResNet era, He Kaiming already discussed the relationship between pre-LayerNorm, post-LayerNorm, and training stability.”
Source→“Let's not forget that Kaiming He at the time was 10% above second place on ImageNet. You either win with your fists — if you can't, then you need persuasion. The AI for AI system needs to propose a new architecture that can improve performance by 10 points, not just 1%.”
Source→“We'd read Kaiming's paper and think the idea was so natural — almost as if it should have always been designed this way.”
Source→AI-extracted from podcast / newsletter / paper summaries. May contain errors.