Changgee Chang, PhD

Dr. Changgee Chang is an Assistant Professor in Department of Biostatistics and Health Data Science. He received a PhD in Statistics from University of Chicago. Prior to joining Indiana University, he has been trained as a postdoctoral researcher and a research associate at University of Pennsylvania. His research interests include developing statistical methodologies for Alzheimer disease research and integrative analysis of multi-omics and neuroimaging data. He is also interested in developing privacy preserving federated learning algorithms for integrative analysis of multi-site EHR data.

1. C. Chang, Z. Bu, and Q. Long (2022) CEDAR: Communication Efficient Distributed Analysis for Regressions. Biometrics, In Press.
2. Y. Zhao, C. Chang, J. Zhang, and Z. Zhang (2022) Genetic underpinnings of brain structural connectome for young adults, Journal of the American Statistical Association, In Press.
3. C. Chang, Y. Deng, X. Jiang, and Q. Long (2020) Multiple imputation for analysis of incomplete data in distributed health data networks. Nature Communications, 11(1), 1-11.
4. C. Chang, J. Jang, A. Manatunga, A. Taylor and Q. Long (2020) A Bayesian Latent Class Model to Predict Kidney Obstruction in the Absence of Gold Standard, Journal of the American Statistical Association, 115:532, 1645-1663.
5. C. Chang, S. Kundu, and Q. Long (2018), Scalable Bayesian Variable Selection for Structured High-Dimensional Data, Biometrics, 74:1372-1382.