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Math @ Duke





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Xiuyuan Cheng, Associate Professor

Xiuyuan Cheng

As an applied analyst, I develop theoretical and computational techniques to solve problems in high-dimensional statistics, signal processing and machine learning.

Contact Info:
Office Location:  120 Science Drive, 293 Physics Building, Durham, NC 27708
Office Phone:  (919) 600-2825
Email Address: send me a message
Web Page:  https://services.math.duke.edu/~xiuyuanc/

Education:

Ph.D.Princeton University2013
Recent Publications   (More Publications)

  1. Tan, Y; Zhang, Y; Cheng, X; Zhou, X-H, Statistical inference using GLEaM model with spatial heterogeneity and correlation between regions., Scientific Reports, vol. 12 no. 1 (October, 2022), pp. 16630 [doi]  [abs]
  2. Zhao, J; Jaffe, A; Li, H; Lindenbaum, O; Sefik, E; Jackson, R; Cheng, X; Flavell, RA; Kluger, Y, Detection of differentially abundant cell subpopulations in scRNA-seq data., Proceedings of the National Academy of Sciences of the United States of America, vol. 118 no. 22 (June, 2021), pp. e2100293118 [doi]  [abs]
  3. Zhang, Y; Cheng, X; Reeves, G, Convergence of Gaussian-smoothed optimal transport distance with sub-gamma distributions and dependent samples, 24th International Conference on Artificial Intelligence and Statistics (Aistats), vol. 130 (2021)
  4. Li, Y; Cheng, X; Lu, J, Butterfly-net: Optimal function representation based on convolutional neural networks, Communications in Computational Physics, vol. 28 no. 5 (November, 2020), pp. 1838-1885 [doi]  [abs]
  5. Mhaskar, HN; Cheng, X; Cloninger, A, A Witness Function Based Construction of Discriminative Models Using Hermite Polynomials, Frontiers in Applied Mathematics and Statistics, vol. 6 (August, 2020) [doi]  [abs]
Recent Grant Support

  • RTG: Training Tomorrow's Workforce in Analysis and Applications, National Science Foundation, 2021/07-2026/06.      
  • Bridging Statistical Hypothesis Tests and Deep Learning for Reliability and Computational Efficiency, Georgia Tech Research Corporation, 2022/01-2024/12.      
  • NSF-BSF: Group Invariant Graph Laplacians: Theory and Computations, National Science Foundation, 2020/07-2024/06.      
  • Sloan Foundation Fellowship for Xiuyuan Cheng in Mathematics, Alfred P. Sloan Foundation, 2019/09-2023/09.      
  • Efficient Methods for Calibration, Clustering, Visualization and Imputation of Large scRNA-seq Data, Yale University, 2019/05-2023/01.      
  • HDR TRIPODS: Innovations in Data Science: Integrating Stochastic Modeling, Data Representation, and Algorithms, National Science Foundation, 2019/10-2022/09.      
  • CDS&E: Structure-aware Representation Learning using Deep Networks, National Science Foundation, DMS-NSF-1820827-01, 2018/07-2022/06.      
  • Collaborative Research: Geometric Analysis and Computation of Generative Models, National Science Foundation, DMS-1818945, 2018/07-2022/06.      

 

dept@math.duke.edu
ph: 919.660.2800
fax: 919.660.2821

Mathematics Department
Duke University, Box 90320
Durham, NC 27708-0320