Zhengxin Zhang ☕️
Zhengxin Zhang

Phd student at Center for Mathematics

Cornell University

About Me

I am a final year PhD student in Applied Mathematics at Cornell University, where I am fortunate to be advised by Ziv Goldfeld. My research interests include mathematical theories for machine learning and high dimensional statistics, with a particular focus on optimal transport. My recent focus centers on the Gromov-Wasserstein distance, which is a fascinating interplay between classial optimal transport and metric geometry.

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Interests
  • Optimal Transport
  • Statistical learning theory
  • Artificial Intelligence
Education

  • PhD in Applied Mathematics

    Cornell University

  • BS in Mathematics and Applied Mathematics

    Shanghai Jiao Tong University

Publications
Zhengxin Zhang, Ziv Goldfeld, Kristjan Greenewald, Youssef Mroueh, Bharath K Sriperumbudur (2024). Gradient Flows and Riemannian Structure in the Gromov-Wasserstein Geometry. arXiv preprint arXiv:2407.11800, accepted at Foundations of Computational Mathematics.
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Zhengxin Zhang, Ziv Goldfeld, Youssef Mroueh, Bharath K Sriperumbudur (2024). Gromov--Wasserstein distances: Entropic regularization, duality and sample complexity. The Annals of Statistics.
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Zhengxin Zhang, Youssef Mroueh, Ziv Goldfeld, Bharath Sriperumbudur (2022). Cycle consistent probability divergences across different spaces. International Conference on Artificial Intelligence and Statistics.
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Sreejith Sreekumar, Zhengxin Zhang, Ziv Goldfeld (2021). Non-asymptotic performance guarantees for neural estimation of f-divergences. International Conference on Artificial Intelligence and Statistics.
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