Yang Song is a fourth-year PhD student in Stanford AI Lab, working with Prof. Stefano Ermon.
Yang's main research interest lies in the intersection between robust machine learning and generative modeling. He aims to improve the robustness of machine learning models by understanding the distribution of anomalous inputs using generative models, and detecting/defending against them accordingly. In order to capture the distributions better, Yang also works on new model architectures and training methods for building more flexible and expressive generative models.
Yang obtained his Bachelor of Science degree in Mathematics and Physics from Tsinghua University. He enjoys playing the violin in his leisure time.
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