Chixiang Chen, PhD

Postdoctoral researcher, University of Pennsylvania, 2021.

Ph.D. in Biostatistics, Pennsylvania State University, 2020.

Dr. Chixiang Chen is an Assistant Professor in Biostatistics who joined the Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, University of Maryland School of Medicine since 2021. Dr. Chen has worked across both theoretical and applied areas of statistics, also has extensive interdisciplinary collaborations including clinical trial design and analysis in neuroscience, medicare claim data, electronical health records, imaging data analysis, oncology research, among others.

Dr. Chen has a very solid background in theoretical statistics and a profound understanding of how to use and implement powerful statistics for clinical and biomedical studies. One of his current research interests is proposing a novel and general computational framework to integrate information from external sources to improve the primary analysis. The newly proposed framework makes multiple information borrowing feasible with stable and scalable computation load. Morevoer, Dr.Chen is highly interested in developing distributed algorithms for analyzing large-scale data (federated data or centralized data), statistical methods to improve the Machine Learning (ML) and causal inference in clinical research, with broad applications in different data structure (bulk RNA-seq, single-cell RNA-seq, etc.).

Please find details from my Personal Website: https://sites.google.com/view/chixiangchen/home

Statistical Method: Data/Information Integration; Causal inference and machine learning; Distributed learning in a large-scale data; Cell Type Deconvolution and single cell data analysis. Biomedical Studies: Clinical studies in neuroscience; Aging; Alzheimer's disease and Rehabilitation of older adults; Brain aging; Single-cell transcriptomics

Selected Publications in Biostatistics and Bioinformatics (* corresponding author):

• Chen, C.*, Wang, M., and Chen, S. (2023). An efficient data integration scheme to synthesize information from multiple secondary outcomes to the main data analysis. Biometrics. Accepted. https://doi.org/10.1111/biom.13858
• Chen, C., Shen, B., Zhang, L., Yu, T., Wang, M., Wu, R. (2023). DRDNetPro: A cartographic tool to predict Disease Risk-associated pseudo-Dynamic Networks from tissue specific gene expression. Bio-protocol. 13(1), e4583.
• Chen, C.*, Leung, Y., Ionita, M., Wang, L.-S., and Li, M. (2022). Omnibus and Robust Deconvolution Scheme of Bulk RNA Sequencing Data via Integrating Multiple Single-cell reference sets and Prior Biological Knowledge. Bioinformatics. 38(19), 4530–4536.

• Chen, C.*, Han, P., and He, F. (2022). Improving main analysis by borrowing information from auxiliary data. Statistics in Medicine. 41(3):567-579. 

• Chen, C., Jiang, L., Shen, B., Wang, M., Griffin, C., Chinchilli, V., and Wu, R. (2021). A computational atlas of tissue-specific regulatory networks. Frontiers in Systems Biology. 1:764161. doi:10.3389/fsysb.2021.764161.
• Chen, C., Shen, B., Liu, A., Wu, R. and Wang, M. (2021). A multiple robust propensity score method for longitudinal analysis with intermittent missing data. Biometrics, 77(2), 519-532.

Selected Publications in interdisciplinary science:

• Chryssikos, T., Stokum, J. A., Ahmed, A. K., Chen, C., Wessell, A., Cannarsa, G., ... & Aarabi, B. (2023). Surgical Decompression of Traumatic Cervical Spinal Cord Injury: A Pilot Study Comparing Real-Time Intraoperative Ultrasound After Laminectomy With Postoperative MRI and CT Myelography. Neurosurgery, 92(2), 353-362.
• Aarabi, B.,Chen, C., Simard, J. M., Chryssikos, T., Stokum, J. A., Sansur, C. A., ... & Schwartzbauer, G. T. (2022). Proposal of a Management Algorithm to Predict the Need for Expansion Duraplasty in American Spinal Injury Association Impairment Scale Grades A–C Traumatic Cervical Spinal Cord Injury Patients. Journal of neurotrauma, 39(23-24), 1716-1726.
• Carney, C. P., Kapur, A., Anastasiadis, P., Ritzel, R. M., Chen, C., Woodworth, G. F., ... & Kim, A. J. (2022). Fn14-Directed DART Nanoparticles Selectively Target Neoplastic Cells in Preclinical Models of Triple-Negative Breast Cancer Brain Metastasis. Molecular Pharmaceutics. Accepted.
• Mo, C., Wang, J., Ye, Z., Ke, H., Liu, S., Hatch, K., Gao, S., Magidson, J., Chen, C., ... & Chen, S. (2022). Evaluating the causal effect of tobacco smoking on white matter brain aging: a two‐sample Mendelian randomization analysis in UK Biobank. Addiction. Accepted.
• Ye, Z., Mo, C., Ke, H., Yan, Q., Chen, C., Kochunov, P., ... & Ma, T. (2022). Meta-analysis of transcriptome-wide association studies across 13 brain tissues identified novel clusters of genes associated with nicotine addiction. Genes, 13(1), 37.
• Bluethmann, S. M., Wang, M., Wasserman, E., Chen, C., Zaorsky, N. G., Hohl, R. J., & McDonald, A. C. (2020). Prostate cancer in Pennsylvania: The role of older age at diagnosis, aggressiveness, and environmental risk factors on treatment and mortality using data from the Pennsylvania Cancer Registry. Cancer medicine, 9(10), 3623-3633.
• Gardner, A. W., Montgomery, P. S., Wang, M., Chen, C., Kuroki, M., & Kim, D. J. K. (2019). Vascular inflammation, calf muscle oxygen saturation, and blood glucose are associated with exercise pressor response in symptomatic peripheral artery disease. Angiology, 70(8), 747-755.