Chong Wu

Portrait of Chong Wu 

Chong Wu

Assistant Professor
Department of Statistics
Florida State University

Research interest: high-dimensional data, statistical genetics, big data, and machine learning

Curriculum Vitae (Aug 8, 2018)

GitHub

Google Scholar


My research is mainly driven by the problems arising from genetics and genomics. If you have some massive and messy genetics and genomics data (such as GWAS, DNA methylation, and human microbiome data) and need to find a biostatistician to analyze your data, please do not hesitate to contact me.

I am seeking highly self-motivated students to join my research group. No prior knowledge in statistical genetics is required, but you should have a strong interest in research.

Short Bio

Currently, 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 the Huazhong University of Science and Technology in 2013.

Publications [by topic]

  1. Wu, C.*, Xu, G., and Pan, W.* (2017+).
    An adaptive test on high dimensional parameters in generalized linear models. Accepted by Statistica Sinica. (* Corresponding author)

  2. Zhu, L., Li, Y., Chen, Y., Carrera, C., Wu, C., and Fork, A. (2018).
    Comparison between two post-dentin bond strength measurement methods. Scientific Reports, 8(1):2350. (IF: 4.3)

  3. Wu, C. and Pan, W. (2018).
    Integrating eQTL data with GWAS summary statistics in pathwaybased analysis. Accepted by Genetic Epidemiology, early online.
    (This paper won a poster talk (top 24 posters among about 3000 posters) at ASHG 2017 Annual Meeting.)

  4. Park, J.Y., Wu, C., Basu, S., McGue, M., and Pan, W. (2018).
    Adaptive SNP set association testing in generalized linear mixed models with application to family studies. Behavior Genetics, 48(1):55–66. (IF: 2.4)

  5. Xu, Z., Wu, C., Wei, P., and Pan, W. (2017+).
    A powerful framework for integrating eQTL and GWAS summary data. Accepted by Genetics, early online. (IF: 4.6)

  6. Liu, B., Wu, C., Shen, X., and Pan, W. (2017).
    A novel and efficient algorithm for de novo discovery of mutated driver pathways. Annals of Applied Statistics, 17(3):1481–1512.

  7. Xu, Z., Wu, C., Pan, W., and Alzheimer’s Disease Neuroimaging Initiative (ADNI). (2017).
    Imaging-wide association study: integrating imaging endophenotypes in GWAS. NeuroImage, 159:159–169.
    (IF: 5.8. This paper won a platform presentation at the American Society of Human Genetics (ASHG) 2017 Annual Meeting.)

  8. 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(188):1–25.
    (* Co-first author. IF: 5.0, a leading journal in machine learning area.)

  9. Wu, C., Chen, J., Kim, J., and Pan, W. (2016).
    An adaptive association test for microbiome data. Genome Medicine, 8(1):1–12.
    (IF: 7.1. This paper won the 2016 Joint Statistical Meetings (JSM) Distinguished Student Paper Award on Statistics in Genomics and Genetics Section.)

  10. Wu, C., Demerath, E. W., Pankow, J. S., Bressler, J., Fornage, M., Grove, M. L., Chen, W., and Guan, W. (2016).
    Imputation of missing covariate values in epigenome-wide analysis of DNA methylation data. Epigenetics, 11(2):132–139.
    (IF: 4.4, the official journal of the DNA Methylation Society.)

  11. Bose, M., Wu, C., Pankow, J. S., Demerath, E. W., Bressler, J., Fornage, M., Grove, M. L., Mosley, T. H., Hicks, C., North, K., Kao, W. H., Zhang, Y., Boerwinkle, E., and Guan, W. (2014).
    Evaluation of microarray-based DNA methylation measurement using technical replicates: the Atherosclerosis Risk In Communities (ARIC) Study. BMC Bioinformatics, 15(1):1–10. (IF: 2.4)

Selected Software

  • 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.

Teaching

For me, teaching can be described as a rewarding and fulfilling experience. I am the instrcutor for the following courses.

Selected Presentations

I enjoy sharing ideas and presenting my works. I usually atend JSM, ENAR, and ASHG each year.

Selected Awards

  • 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
201C OSB, 117 N. Woodward Ave.
P.O. Box 3064330, Tallahassee, FL, 32306-4330
E-mail: chongwu@stat.fsu.edu