Xin Xing

List of courses taught

• CMDA 3654 Lecture: Intro to Data Analytics & Visualization, Fall, 2020

List of research projects

• Bioinformatics: metagenomics, single cell, epigenomics, neuroimaging
• Statistics: minimax nonparametric testing, smoothing spline, dimension reduction, controlled variable selection
• Machine learning: neural network, transfer learning

• Xin Xing, Meimei Liu, Wenxuan Zhong, Ping Ma. (2020). Minimax Nonparametric Parallelism Test, Journal of Machine Learning Research, 21(94):1-47.
• Xin Xing, Long Sha, Pengyu Hong, Zuofeng Shang, Jun S. Liu (2020). Probabilistic Connection Importance Inference and Lossless Compression of Deep Neural Networks. International Conference on Learning Representations (ICLR)
• Xin Xing, Yu Gui, Chengguang Dai, Jun S. Liu (2020). Deep Gaussian Mirror for Controlled Variable Selection, IEEE ICMLA, 2020.
• Terry Ma, Di Xiao, Xin Xing (Corresponding author) (2019). MetaBMF: A Scalable Binning Algorithm for Large-scale Reference-free Metagenomic Studies. Bioinformatics.
• Xin Xing, Jun S. Liu,Wenxuan Zhong (2018). MetaGen: reference-free learning with multiple metagenomic samples. Genome biology, 18 (1), 187, 2018.
• Terry Ma, Xin Xing (2018). A Scalable Reference-Free Metagenomic Binning Pipeline. International Symposium on Bioinformatics Research and Applications, 79-83.
• Yiwen Liu, Xin Xing, Wenxuan Zhong (2018). Sufficient Dimension Reduction for Tensor Data. Handbook of Big Data Analytics, Springer.
• Wenxuan Zhong, Xin Xing, Kenneth Suslick (2015). Tensor Sufficient Dimension Reduction WIREs Computational Statistics, 7(3), 178-184.
• Xin Xing, Jinjin Hu, and Yaning Yang (2014). Robust minimum variance portfolio with L-infinity constraints, Journal of Banking and Finance, 46, 107-117.
• Xin Xing, Meimei Liu, Weiping Zhang (2014). Joint Semiparametric Mean-Covariance Modeling by Moving Average Cholesky Decomposition for Longitudinal Data, Journal of University of Science and Technology of China, 43(8), 607-621.