Chong Wu

Portrait of Chong Wu 

Chong Wu

Assistant Professor
Department of Statistics
Florida State University

Research interest: Statistical genetics/genomics, integrative analysis, big data, machine learning, causal inference, and high-dimensional inference.

Curriculum Vitae (Feb, 2021)

GitHub

Google Scholar

Short Bio

I am an Assistant Professor in the Department of Statistics at Florida State University. Prior to FSU, I was a biostatistics Ph.D. student at the University of Minnesota, co-advised by Profs. Weihua Guan and Wei Pan. I received my bachelor's degree in Applied Math from Huazhong University of Science and Technology in 2013.

My research interests are in statistical genetics and genomics, statistical learning, and machine learning. I have obtained diverse training and experiences in developing statistical methods and algorithms for analyzing multiple types of genetic and genomic data, including genome-wide association study (GWAS) data, DNA methylation data, and human microbiome data. My work includes gene- and pathway-based association testing, integrative -omics analysis, new algorithms in clustering, Mendelian randomization, and polygenic risk scores. To practice and facilitate reproducible research, I have developed and currently maintain several software (most in R packages) and their online manuals. My recent work involves integrative analysis of GWAS with multiple sources of omics data.

I am seeking highly self-motivated students to join my research group. If you are interested, feel free to send me an email or stop by my office.

News

  • 2021-05: Our COVID-19 integrative analysis paper has been accepted by Genetics in Medicine.

  • 2021-01: Our R03 proposal (Novel Statistical Methods for Multi-omics Data Integration in Alzheimer's Disease) has been funded by NIA.

Selected Publications [by topic]

* Corresponding author

  1. He, Y., Xu, G., Wu, C., and Pan, W. (2021)
    Asymptotically Independent U-Statistics in High-Dimensional Testing. Annals of Statistics, 49(1), 154-181.

  2. Wu, C.*, Bradley J., Li, Y., Wu, L., and Deng, HW. (2021)
    A gene-level methylome-wide association analysis identifies novel Alzheimer’s disease genes. Bioinformatics.

  3. Wu, C.*, Xu, G., Shen, X., and Pan, W.* (2020)
    A regularization-based adaptive test for high-dimensional generalized linear models. Journal of Machine Learning Research, 21(128), 1-67.

  4. Wu, C. (2020)
    Multi-trait genome-wide analyses of the brain imaging phenotypes in UK Biobank. Genetics, 215(4), 947-958.
    (Highlight in Genetics August issue; presented as a platform presentation at ASHG 2019 Annual Meeting)

  5. Wu, C.* and Pan, W.* (2019)
    Integration of methylation QTL and enhancer-target gene maps with schizophrenia GWAS summary results identifies novel genes. Bioinformatics, 35(19), 3576-3583.

  6. Wu, C., Chen, J., Kim, J., and Pan, W. (2016) An adaptive association test for microbiome data. Genome Medicine, 8(1), 1-12.

  7. Wu, C.#, Kwon, S.#, Shen, X., and Pan, W. (2016). A new algorithm and theory for penalized regression-based clustering. Journal of Machine Learning Research, 17(1), 6479-6503. #, co-first author

Selected Software

We put all recent developed software into a lab github page.

  • prclust: Penalized Regression-Based Clustering Methods;

  • MiSPU: Microbiome Based Sum of Powered Score (MiSPU) Tests;

  • GLMaSPU: Adaptive Tests on High Dimensional Parameters in Generalized Linear Models;

  • IWAS: Imaging-Wide Association Study;

  • TWAS: Integrating eQTL and GWAS data;

  • aSPUpath2: Integrating eQTL data with GWAS summary statistics in pathway-based analysis.

Grants

  • R03 AG070669, NIA
    Contact PI, (Wu and Bradley), 01-01-21 – 12-31-22
    Novel Statistical Methods for Multi-omics Data Integration in Alzheimer's Disease

  • The Committee on Faculty Research Support, FSU
    PI, 05-07-20 – 06-30-20
    Novel Machine Learning Methods for Alzheimer’s Disease

  • First Year Assistant Professor Grant, FSU
    PI, 05-08-19 - 08-06-19
    Novel Statistical Methods for Transcriptome-wide Association Studies

Teaching

The opportunity for teaching is one of the key reasons I love academia. For me, teaching can be described as a rewarding and fulfilling experience. I am the instructor for the following courses.

Selected Presentations

I enjoy sharing ideas and presenting my works. I attend JSM, ENAR, and ASHG regularly.

Awards

  • Dean's Faculty Travel Award, Florida State University, 2020

  • ENAR Distinguished Student Paper Award, 2019

  • James R. Boen Student Achievement Award, Division of Biostatistics, University of Minnesota, 2018

  • Pre-Doctoral Trainee Award, Association of Chinese Geneticists in America (ACGA), 2017

  • Elected to Delta Omega (Public Health Honorary Society), 2017

  • Elected to Simga Xi (The Scientific Research Society), 2017

  • JSM Distinguished Student Paper Award on Statistics in Genomics and Genetics Section, 2016

  • Doctoral Dissertation Fellowship, University of Minnesota, 2016

  • Travel Award, Computational Neuroscience Summer School, Statistical and Applied Mathematical Sciences Institute, 2015

  • Dean's Ph.D. Scholarship, University of Minnesota, 2013

  • Honorable Mention in Mathematical Contest in Modeling, Consortium for Mathematics and Its Application, 2012

  • National Scholarship, Ministry of Education, China, 2011

Contact

Chong Wu
314 OSB, 117 N. Woodward Ave.
P.O. Box 3064330, Tallahassee, FL, 32306-4330
E-mail: cwu3@fsu.edu