Dr. Tianzhou Charles Ma
Assistant Professor, Epidemiology and Biostatistics
Other Affiliations: SPH
Building: School of Public Health | Room: 2234M
Phone: (301) 405-6421 |
Tianzhou (Charles) Ma's personal website
CV / Resume
PDF icon TianzhouMa_CV.pdf

Dr. Tianzhou (Charles) Ma is an Assistant Professor in Biostatistics at the Department of Epidemiology and Biostatistics of the School of Public Health at University of Maryland. He received his PhD in Biostatistics from the University of Pittsburgh in 2018 and a MS in Biostatistics from Yale University in 2013. Dr. Ma’s research focuses on statistical methods in genomics and bioinformatics, meta-analysis and omics data integration, statistical machine learning, Bayesian analysis, high-dimensional variable selection, as well as their application in cancer, psychiatry (aging and depression) and epidemiology fields. His work has appeared in Journal of the Royal Statistical Society, Statistica Sinica, Bioinformatics, Journal of Computational Biology, Proceedings of the National Academy of Sciences, Nucleic Acid Research, Clinical Cancer Research, Oncogene, Biological Psychiatry, Obstetrics & Gynecology. He is open-minded and actively seeking for collaborations with researchers from various fields, to understand the objectives of their projects, provide consultation in study design and help analyze the data.  

Education and Training

2013-2018 Ph.D. in Biostatistics, University of Pittsburgh

2011-2013 M.S. in Biostatistics, Yale University

2007-2010 B.S. in Genetics and Biotechnology, University of Toronto


EPIB 661: Applied Multivariate Data Analysis

EPIB 664: Missing Data Analysis

EPIB 652: Categorical Data Analysis

Honors and Awards

FY20-21 FSRA Award, UMD Graduate School, 2019

Delta Omega Membership, Delta Omega Honorary Society in Public Health, 2018

Student Paper Award, American Statistical Association Section on Bayesian Statistical Science (SBSS), 2017

Student of the Year, American Statistics Association (ASA) Pittsburgh chapter, 2017

Best Paper Award, Dahshu Data Science Symposium: Computational Precision Health, 2017

Best Student Presentation Award, Department of Biostatistics, University of Pittsburgh, 2017

Outstanding Graduate Student Researcher Award, Department of Biostatistics, University of Pittsburgh, 2016

Travel Award to attend "Optimization Opening Workshop" , Statistical and Applied Mathematical Sciences Institute, 2016

Dean's Day Poster Competition Award, Graduate School of Public Health, University of Pittsburgh, 2015

Dean's list, Faculty of Arts and Science, University of Toronto, 2008-2010

University College Scholarship, University College, University of Toronto, 2008-2010


Research Group: https://www.umdbright.com/

Google Scholar: https://scholar.google.com/citations?user=28ddsXsAAAAJ&hl=en&authuser=1

ResearchGate: https://www.researchgate.net/profile/Tianzhou_Ma

My Bibliography at NCBI:  https://www.ncbi.nlm.nih.gov/sites/myncbi/1J7h-bJwltc9jj/bibliography/56494084/public/?sort=date&direction=descending

Selected Publications:

Ma, T., Ren, Z. and Tseng, GC. (2020). Variable screening with multiple studies. Statistica Sinica, 30(2): 925-953. 

Lin, CW, Chang LC, Ma, T., Oh, H., French, B., ..., Tseng, GC and Sibille, E. (2020). Older molecular brain age in severe mental illness. Molecular Psychiatry, 1-11. 

Ma, T.*, Huo, Z.*, Kuo, A.*, Zhu, L., Fang, Z., Zeng, X., Lin, C., Liu. S., Wang, L., Liu, P., Rahman, T., Chang, L., Kim, S., Li, J., Park, Y., Song, C. and Tseng, GC. (2019). MetaOmics - Comprehensive Analysis Pipeline and Web-based Software Suite for Transcriptomic Meta-Analysis. Bioinformatics, 35(9): 1597-1599.
Zhu, L., Huo, Z., Ma, T., Osterreich, S and Tseng GC. (2019). Bayesian indicator variable selection to incorporate hierarchical overlapping group structure in multi-omics applications. Annals of Applied Statistics, 13(4): 2611-2636.
Fang, Z., Ma, T., Tang, G., Zhu, L., Yan, Q., Wang, T., Celedón, J.C., Chen, W., Tseng, G.C. and Hancock, J. (2018). Bayesian integrative model for multi-omics data with missingness. Bioinformatics, 34(22):  3801-3808.
Scifo, E., Pabba, M., Kapadia, F., Ma, T., Lewis, D.A., Tseng, G.C. and Sibille, E. (2018). Sustained molecular pathology across episodes and remission in major depressive disorder. Biological psychiatry83(1), pp.81-89.

Ma, T., Liang, F. and Tseng, G.C. (2017) Biomarker detection and categorization in ribonucleic acid sequencing meta‐analysis using Bayesian hierarchical models. Journal of the Royal Statistical Society: Series C (Applied Statistics)66(4), pp.847-867. (reported on [RNA-Seq Blog]

Ma, T., Liang, F., Oesterreich, S. and Tseng, G.C. (2017) A Joint Bayesian Model for Integrating Microarray and RNA Sequencing Transcriptomic Data. Journal of Computational Biology24(7), pp.647-662.

French, L., Ma, T., Oh, H., Tseng, G.C. and Sibille, E. (2017) Age-related gene expression in the frontal cortex suggests synaptic function changes in specific inhibitory neuron subtypes. Frontiers in Aging Neuroscience9, p.162.

Andersen, C.L., Sikora, M.J., Boisen, M.M., Ma, T., Christie, A., Tseng, G., Park, Y.S., Luthra, S., Chandran, U., Haluska, P. and Mantia-Smaldone, G. (2017) Active estrogen receptor-alpha signaling in ovarian cancer models and clinical specimens. Clinical Cancer Research, pp.clincanres-1501.

Zhang, L., Ma, T., Brozick, J., Babalola, K., Budiu, R., Tseng, G., & Vlad, A. M. (2016). Effects of Kras activation and Pten deletion alone or in combination on MUC1 biology and epithelial-to-mesenchymal transition in ovarian cancer. Oncogene35(38), 5010.

Chen, C. Y., Logan, R. W., Ma, T., Lewis, D. A., Tseng, G. C., Sibille, E., & McClung, C. A. (2016). Effects of aging on circadian patterns of gene expression in the human prefrontal cortex. Proceedings of the National Academy of Sciences113(1), 206-211. (High Attention Paper, 99th
percentile, [News on National Public Radio (NPR)])

Sanei-Moghaddam, A., Ma, T., Goughnour, S.L., Edwards, R.P., Lounder, P.J., Ismail, N., Comerci, J.T., Mansuria, S.M. and Linkov, F. (2016). Changes in hysterectomy trends after the implementation of a clinical pathway. Obstetrics & Gynecology127(1), pp.139-147.

Liao, S., Hartmaier, R.J., McGuire, K.P., Puhalla, S.L., Luthra, S., Chandran, U.R., Ma, T., Bhargava, R., Modugno, F., Davidson, N.E. and Benz, S. (2015). The molecular landscape of premenopausal breast cancer. Breast Cancer Research17(1), p.104. (discussed
in an interview; [Nature, 527: S108-109])

Liu, S., Tsai, W.H., Ding, Y., Chen, R., Fang, Z., Huo, Z., Kim, S., Ma, T., Chang, T.Y., Priedigkeit, N.M. and Lee, A.V. (2015). Comprehensive evaluation of fusion transcript detection algorithms and a meta-caller to combine top performing methods in paired-end RNA-seq data. Nucleic acids research44(5), pp.e47-e47.