Hi! I am a Ph.D. student in Computational and Applied Mathematics at the University of Chicago, where I am fortunate to be advised by Daniel Sanz-Alonso. Before coming to Chicago, I received my B.S. in Mathematics and Applied Mathematics from Shanghai Jiao Tong University.
My research focuses on the mathematics of data science and scientific machine learning, with an emphasis on operator learning, high-dimensional probability and statistics, and Monte Carlo methods. More broadly, I am interested in how information and structure shape the limits of learning and computation.
Publications and Preprints
- Concentration inequalities for sample cross-covariances. With D. Sanz-Alonso, (2026). [arXiv]
- Convergence rates for learning pseudo-differential operators. With D. Sanz-Alonso, (2026). [arXiv]
- Optimal estimation of structured covariance operators. With O. Al-Ghattas, D. Sanz-Alonso, and N. Waniorek, (2024). [arXiv]
- High-dimensional quasi-Monte Carlo via combinatorial discrepancy. With H. Jiang and N. Kirk.
Journal of Complexity, 96, 102053, 1-23, (2026). [Journal] [arXiv] - Sharp concentration of simple random tensors II: asymmetry. With D. Sanz-Alonso.
Information and Inference, 15(2), 1-46, (2026). [Journal] [arXiv] - On the estimation of Gaussian moment tensors. With O. Al-Ghattas and D. Sanz-Alonso.
Electronic Communications in Probability, 30, 1-15, (2025). [Journal] [arXiv] - Sharp concentration of simple random tensors. With O. Al-Ghattas and D. Sanz-Alonso.
Information and Inference, 14(4), 1-41, (2025). [Journal] [arXiv] - Precision and Cholesky factor estimation for Gaussian processes. With D. Sanz-Alonso.
SIAM/ASA Journal on Uncertainty Quantification, 13(3), 1085-1115, (2025). [Journal] [arXiv] - Covariance operator estimation: sparsity, lengthscale, and ensemble Kalman filters. With O. Al-Ghattas, D. Sanz-Alonso, and N. Waniorek.
Bernoulli, 31(3), 2377-2402, (2025). [Journal] [arXiv] - A machine learning framework for geodesics under spherical Wasserstein-Fisher-Rao metric and its application for weighted sample generation. With Y. Jing, L. Li, and J. Lu.
Journal of Scientific Computing, 98(5), 1-34, (2024). [Journal] [arXiv] - Fluctuation suppression and enhancement in interacting particle systems. With L. Li, (2022). [arXiv]
Teaching
University of Chicago Teaching Assistant
- STAT/CAAM 31511: Monte Carlo Simulation, Spring 2026
- STAT/CAAM 31521: Applied Stochastic Processes, Spring 2025
- STAT/CAAM 31050: Applied Approximation Theory, Spring 2024
- STAT/CAAM 38100: Measure-Theoretic Probability I, Winter 2024
- STAT/CAAM 31150: Inverse Problems and Data Assimilation, Autumn 2023