Scholar
Songzhu Zheng
Google Scholar ID: vq0hpV4AAAAJ
Morgan Stanley
Citations & Impact
Citations
997
H-index
10
i10-index
10
Publications
14
Co-authors
6
list available
Publications
Resume (English only)
Academic Achievements
- Published multiple papers in top conferences such as NeurIPS, ICLR, and ICML, including 'Topological Detection of Trojaned Neural Networks', 'Learning with Feature Dependent Label Noise: a Progressive Approach', 'A Topological Filter for Learning with Label Noise', and 'Error-Bounded Correction of Noisy Labels'.
Research Experience
- Worked as an AI Researcher Intern at Morgan Stanley, responsible for designing DNNs that identify learnable data out of mostly noisy datasets and constructing optimal MBS products with maximized market value using RL.
Education
- PhD in Statistics, 2022 (expected) from Stony Brook University; MA in Statistics, 2017 from Rice University; BS in Statistics, 2015 from Communication University of China.
Background
- A statistics PhD student focusing on robust machine learning methods against label noise or data poisoning attacks. Also interested in applying machine learning to solve financial problems.
Miscellany
- Interests include Artificial Intelligence, Machine Learning, and Statistical Inference.
