Xin (Shayne) Xing

Department of Statistics
Virginia Tech
Emai: xinxing AT vt.edu

Personal Information

I am an Assistant Professor in the Department of Statistics at Virginia Tech. Prior to VT, I worked with Jun Liu as a post-doc in Department of Statistics at Harvard University. I graduated from University of Georgia supervised by Wenxuan Zhong . I received a M.S. and B.S. in statistics supervised by Yaning Yang at University of Science and Technology of China.

Research Interests

Statistics: minimax nonparametric testing, smoothing spline, dimension reduction, controlled variable selection

Machine learning: neural network, domain adaptation, transfer learning

Computational biology: metagenomics, single cell, epigenomics, neuroimaging

Research

Preprints

Minimax Nonparametric Two-sample Test
Xin Xing, Zuofeng Shang, Pang Du, Ping Ma, Wenxuan Zhong, Jun S. Liu
Arxiv

False Discovery Rate Control via Data Splitting
Chenguang Dai, Buyu Lin, Xin Xing, Jun S. Liu
Arxiv

A Scale-free Approach for False Discovery Rate Control in Generalized Linear Models
Chenguang Dai, Buyu Lin, Xin Xing, Jun S. Liu
Arxiv


Publications

Model-based Sparse Coding beyond Gaussian Independent Model
Xin Xing, Rui Xie, Wenxuan Zhong
Computational Statistics and Data Analysis (CSDA), 2021

Controlling False Discovery Rate Using Gaussian Mirrors
Xin Xing, Zhigen Zhao, Jun S. Liu
Journal of the American Statistical Association (JASA), 2021

Minimax Nonparametric Parallelism Test [Software]
Xin Xing, Meimei Liu, Ping Ma, Wenxuan Zhong
Journal of Machine Learning Research (JMLR), 2020

Reduction of mNAT1/hNAT2 Contributes to Cerebral Endothelial Necroptosis and Aβ Accumulation in Alzheimer’s Disease
Chengyu Zou, Lauren Mifflin, Zhirui Hu, Tian Zhang, Bing Shan, Huibing Wang, Xin Xing, Hong Zhu, Xian Adiconis, Joshua Z Levin, Fupeng Li, Chuan-Fa Liu, Jun S Liu, Junying Yuan
Cell Reports, 2020

Neural Gaussian Mirror for Controlled Feature Selection in Neural Networks
Xin Xing, Yu Gui, Chenguang Dai, Jun S. Liu
IEEE ICMLA, 2020

Probabilistic Connection Importance Inference and Lossless Compression of Deep Neural Networks
Xin Xing, Long Sha, Pengyu Hong, Zuofeng Shang, Jun S. Liu
International Conference on Learning Representations (ICLR), 2020

Asymptotic Analysis of Sampling Estimators for Randomized Numerical Linear Algebra Algorithms
Ping Ma, Xinlian Zhang, Xin Xing, Jinyi Ma, Michael Mahoney
International Conference on ArtificialIntelligence and Statistics (AISTATS), 2020

MetaBMF: A Scalable Binning Algorithm for Large-scale Reference-free Metagenomic Studies [Software]
Terry Ma, Di Xiao, Xin Xing (Corresponding Author)
Bioinformatics, 2019

MetaGen: Reference-free Learning with Multiple Metagenomic Samples [Software]
Xin Xing, Jun S. Liu, Wenxuan Zhong
Genome Biology, 2018

A Scalable Reference-Free Metagenomic Binning Pipeline
Terry Ma, Xin Xing
International Symposium on Bioinformatics Research and Applications, 2018

Sufficient Dimension Reduction for Tensor Data
Yiwen Liu, Xin Xing, Wenxuan Zhong
Handbook of Big Data Analytics, Springer, 2018

Tensor Sufficient Dimension Reduction
Wenxuan Zhong, Xin Xing, Kenneth Suslick
WIREs Computational Statistics, 2015

Robust Minimum Variance Portfolio with L-infinity Constraints
Xin Xing, Jinjin Hu, Yaning Yang
Journal of Banking & Finance, 2014

Joint Semiparametric Mean-Covariance modeling by Moving Average Cholesky Decomposition for Longitudinal Data
Xin Xing, Meimei Liu, Weiping Zhang
Journal of University of Science and Technology of China, 2013


Grants

NVIDIA GPU Grant for Accelerated Data Science 2019


Research Highlights

Research is highlighted on the website of graduate school of UGA.

Research is highlighted on the website of Pittsburgh Supercomputer Center.

Teaching

Semester Course Course Title
Spring 2022 STAT 4984 Deep Learning
Fall 2021 CMDA 3654 Intro to Data Analytics & Visualization
Spring 2021 CMDA 3654 Intro to Data Analytics & Visualization
Fall 2020 CMDA 3654 Intro to Data Analytics & Visualization