Epidemiology & Public Health
Education and Training
Postdoctoral researcher, University of Pennsylvania, 2021.
Ph.D. in Biostatistics, Pennsylvania State University, 2020.
Please find details from my Personal Website: https://sites.google.com/view/chixiangchen/home
Information Integration; Causal Inference; Network Analysis; High-dimensional Data; Cell Type Deconvolution and single cell data analysis.
- Chen, C., Wang, M., Wu, R. and Li, R. (2021). A robust consistent information criterion for model selection based on empirical likelihood, Statistica Sinica. Accepted.
- 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.
- Chen, C., Shen, B., Zhang, L., Xue, Y. and Wang, M. (2019). Empirical-likelihood-based criteria for model selection on marginal analysis of longitudinal data with dropout missingness.Biometrics, 75(3), 950-965.
- Chen, C., Jiang, L., Fu, G., Wang, M., Wang, Y., Shen, B., Liu, Z., Wang, Z., Hou, W., Berceli, S. and Wu, R. (2019). An omnidirectional visualization model of personalized gene regulatory networks, npj Systems Biology and Applications, 5(1), 1-11.
- Shen, B., Chen, C., Liu, D., Datta, S., Ghahramani, N., Chinchilli, V. M. and Wang, M (2021). A joint modeling of longitudinal data with informative cluster size adjusted for zero-inflation and terminal event. Statistics in Medicine, 40(21): 4582-4596.
- Gandhi, C. K.,Chen, C., Amatya, S., Yang, L., Fu, C., Zhou, S., Wu, R., Buendía-Roldan, I., Selman, M., Pardo, A. A., and Floros, J. (2021). SNP and haplotype interaction models reveal association of surfactant protein gene polymorphisms with hypersensitivity pneumonitis of Mexican population. Frontiers in Medicine, 7, 1043.
- Wang, M., Long, Q., Chen, C. and Zhang, L. (2020). Assessing predictive accuracy of survival regressions subject to non-independent censoring. Statistics in Medicine, 39(4), pp.469-480.
- Gardner, A., Montgomery, P., Wang, M., Chen, C., Kuroki, M. and Kim, D. (2019). Greater exercise pressor response is associated with impaired claudication outcomes in symptomatic peripheral artery disease. Angiology, 70(3), 220-228.
Dr. Chen has broad interests in both theoretical methodology development and statistical application in multidisciplinary areas. Recently, he is especially interested in developing robust statistical frameworks to integrate information from multiple data sources, with applications in both clinical and genomics studies. Many ongoing works involve survival analysis, causal inference, single-cell data analysis, among others, under the umbrella of the proposed framework.
Another aspect he is working on is to develop a statistical framework to recover dynamic networks from static-state data. The collection of temporal or perturbed data is a prerequisite for reconstructing dynamic networks. However, these types of data are seldom available for genomic studies in medicine, significantly limiting the use of dynamic networks to characterize the biological principles underlying human health and diseases. One proposed framework from Dr. Chen's team makes the reconstruction possible from steady-state data by introducing an agent and incorporating a varying coefficient model with ordinal differential equations. Multiple networks can be inferred corresponding to covariate effects that are linked to known or latent agents, such as disease risk.
In addition, Dr. Chen has experience on model selection, robust longitudinal data analysis, missing data, and other statistical topics with applications in biomedical studies. Besides statistical methodology development, Dr. Chen has worked on multiple projects with collaborators in various disciplines. It ranges from angiology, biochemistry, neuroscience, among others. From past five years with expertise in biostatistics, he denoted himself to data management and preprocessing, modeling and statistical analysis, result evaluation and interpretation as well as intellectual contributions to the work and any publications that result from it.
Dean's Award for Scholarly Achievement, College of Medicine, Penn State Univ. May.2021.
Alumni Society Award, College of Medicine, Penn State Univ. Sep.2019.
JSM Student Paper Award, ASA Nonparametric Section. Jul.2019.
Scholarship Award, the 24th Summer Institute in Statistical Genetics, Univ. of Washington. Jul.2019.
Biopharm-Deming Student Scholar Award, ASA Biopharmaceutical Section and the 74th Annual Deming Conference on Applied Statistics. Dec.2018.
Student Paper Award, ICSA Applied Statistics Symposium. Jun.2018.
Editorial Assistant, ICSA Bulletin 2021 Issue. Dec.2020-present
Session Chair, ENAR 2021 Spring Meeting, Online. Mar.2021
Session Chair, ENAR 2019 Spring Meeting, Philadelphia, PA. Mar.2019
Organizer for Biostatistics Student Seminar, Penn State Univ. Sep.2018-May.2020
Chair, Hershey Chinese Students and Scholars Association. Jan.2018-Sep.2019
Paper Review Service as a Reviewer:
Biometrics, Statistics in Medicine, Journal of Biopharmaceutical Statistics, Biometrical Journal, BMC Medical Research Methodology, European journal of neuroscience, among others
Contributed paper presentation. A Generalized Weighting Scheme to Integrate Infor-
mation from Multiple Auxiliary Records to the Main Study, ENAR Spring Meeting,
Baltimore, MA. Mar.2021
Contributed paper presentation. Informative dynamic ODE-based-network learning
(IDOL) from steady data, ENAR Spring Meeting, Nashville, TN. Mar.2020
Paper award presentation. A robust consistent information criterion for model selec-
tion based on empirical likelihood, JSM, Denver, CO. Jul.2019
Contributed paper presentation. A robust consistent information criterion for model
selection based on empirical likelihood, ENAR Spring Meeting, Philadelphia, PA. Mar.2019
Scholar award poster. A robust consistent information criterion for model selection
based on empirical likelihood, The 74th Annual Deming Conference, Atlantic City, NJ.
Paper award presentation. Empirical likelihood based criteria for model selection on
marginal analysis of longitudinal data with dropout missingness, ICSA Applied Statis-
tics Symposium, New Brunswick, NJ. Jun.2018
Contributed paper presentation. Empirical likelihood based criteria for model selec-
tion on marginal analysis of longitudinal data with dropout missingness, ENAR Spring
Meeting, Atlanta, GA. Mar.2018