portrait

I am a fifth-year PhD student at Courant Institute of Mathematical Sciences, New York University. I am fortunate to be advised by Prof. Jonathan Weare.

My research interest is in analysis, design and application of Monte Carlo sampling methods.

Before my PhD study, I obtained my B.S. degree in Computational Mathematics at Peking University. I worked with Prof. Lei Zhang and Prof. Tiejun Li. I was mostly interested in mathematical modeling of biological systems, which in the end inspires me to study more on stochasticity.

Publications

  • Yifan Chen, Xiaoou Cheng, Jonathan Niles-Weed, Jonathan Weare. Convergence of Unadjusted Langevin in High Dimensions: Delocalization of Bias. arXiv link
    Preprint.

  • Xiaoou Cheng, Jonathan Weare. The surprising efficiency of temporal difference learning for rare event prediction. arXiv link
    Accepted at NeurIPS 2024.

  • Atsushi Shimizu, Xiaoou Cheng, Christopher Musco, Jonathan Weare. Improved Active Learning via Dependent Leverage Score Sampling. OpenReview link arXiv link
    International Conference on Learning Representations (ICLR 2024).
    Invited for oral presentation.

  • Xiaoou Cheng, Maria R. D’Orsogna, Tom Chou. Mathematical Modeling of Depressive Disorders: Circadian Driving, Bistability and Dynamical Transitions. link
    Computational and Structural Biotechnology Journal (2021).

Contact

  • Email: chengxo_at_nyu_edu