Assistant Professor of Mathematics
As an applied analyst, I develop theoretical and computational techniques to solve problems in high-dimensional statistics, signal processing and machine learning.
Appointments and Affiliations
- Assistant Professor of Mathematics
- Office Location: 120 Science Drive, 293 Physics Building, Durham, NC 27708
- Email Address: email@example.com
- Ph.D. Princeton University, 2013
Theory and computation of spectral methods, geometrical data analysis, high dimensional statistics, mathematical analysis of deep neural networks.
- K_MATH 302: Numerical Analysis
- K_MATH 405: Mathematics of Data Analysis and Machine Learning
- MATH 393: Research Independent Study
- MATH 493: Research Independent Study
- MATH 532: Basic Analysis II
- MATH 561: Numerical Linear Algebra, Optimization and Monte Carlo Simulation
- MATH 790-90: Minicourse in Advanced Topics
- Cheng, X; Cloninger, A; Coifman, RR, Two-sample statistics based on anisotropic kernels, Information and Inference (2019) [10.1093/imaiai/iaz018] [abs].
- Cheng, X; Rachh, M; Steinerberger, S, On the diffusion geometry of graph Laplacians and applications, Applied and Computational Harmonic Analysis, vol 46 no. 3 (2019), pp. 674-688 [10.1016/j.acha.2018.04.001] [abs].
- Cheng, X; Qiu, Q; Calderbank, R; Sapiro, G, RoTDCF: Decomposition of convolutional filters for rotation-equivariant deep networks, 7th International Conference on Learning Representations, Iclr 2019 (2019) [abs].
- Cheng, X; Mishne, G; Steinerberger, S, The geometry of nodal sets and outlier detection, Journal of Number Theory, vol 185 (2018), pp. 48-64 [10.1016/j.jnt.2017.09.021] [abs].
- Yan, B; Sarkar, P; Cheng, X, Provable estimation of the number of blocks in block models, International Conference on Artificial Intelligence and Statistics, Aistats 2018 (2018), pp. 1185-1194 [abs].