Songzhu Zheng

Songzhu Zheng

PhD Student of Statistics

Stony Brook University


I’m a statistics PhD student at Stony Brook University. My research focus on robust machine learning methods against label noise or data posioning attack. I’m also interested in the application of machine leanring method to solve financial problem.

Download my resumé.

  • Artificial Intelligence
  • Machine Learning
  • Statistical Inference
  • PhD in Statistics, 2022 (expected)

    Stony Brook University

  • MA in Statistics, 2017

    Rice University

  • BS in Statistics, 2015

    Communication University of China


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(2021). Topological Detection of Trojaned Neural Networks. NeurIPS.


(2021). (Spotlight, +equalcontribution) Learning with Feature Dependent Label Noise: a Progressive Approach. ICLR.

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(2020). (+equal contribution) A Topological Filter for Learning with Label Noise. NeurIPS.

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(2020). Error-Bounded Correction of Noisy Labels. ICML.

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AI Researcher Intern
Morgan Stanley
Jun 2021 – Aug 2021 NYC

Responsibilities include:

  • Design DNN that identifies learnable data out of majority noisy dataset
  • Construct optimal MBS products with maximized market value with RL