Epidemiology and Biostatistics Department
1295 N. Martin
Drachman Hall A228
PO Box: 245211
Tucson AZ 85724
Chengcheng Hu, Ph.D., M.S., is an Associate Professor of Biostatistics and Director of Biostatistics at the University of Arizona Mel and Enid Zuckerman College of Public Health-Phoenix. He is also Director of the Biometry Core on the Chemoprevention of Skin Cancer Project at the University of Arizona Cancer Center and served as Co-Director of the Pattern Analysis and Computational Biology Core on the Targets to Therapeutics in Pancreatic Cancer Project from 2009 to 2010.
Hu joined the UA College of Public Health in 2008. Prior to this he was an assistant professor of Biostatistics at the Harvard School of Public Health from 2002 to 2008. While at Harvard, he also served as senior statistician in the International Maternal Pediatric Adolescent AIDS Clinical Trials Group (IMPAACT).
Hu has worked on multiple federal grants in a broad range of areas including cancer, occupational health, HIV/AIDS, and aging. He has extensive experience in collaborative research, conducting methodological research in the areas of survival analysis, longitudinal data, high-dimensional data, and measurement error. His current methodological interest, arising from studies of viral and human genetics and biomarkers, is to develop innovative methods to investigate the relationship between high-dimensional information and longitudinal outcomes or survival endpoints.
Hu received his Ph.D. and M.S. in Biostatistics from the University of Washington and a M.A. in Mathematics from Johns Hopkins University.
Healy, B.C., De Gruttola, V.G., and Hu, C. (2008). Accommodating uncertainty in tree set for function estimation. Statistical Applications in Genetics and Molecular Biology, 7, Iss. 1, Article 5. Available at: http://www.degruyter.com/view/j/sagmb
Capparelli, E.V., Aweeka, F., Hitti, J., Stek, A., Hu, C., Burchett, S.K., Best, B., Smith, E., Read, J.S., Watts, H., Nachman, S., Thorpe, E.M., Spector, S.A., Jimenez, E., Shearer, W.T., Foca, M., Mirochnick, M., for the PACTG
1026S and P1022 Study Teams (2008). Chronic administration of nevirapine during pregnancy: impact of pregnancy on pharmacokinetics. HIV Medicine 9(4), 214-220.
Read, J.S., Best, B.M., Stek, A.M., Hu, C., Capparelli, E.V., Holland, D.T., Burchett, S.K., Smith, M.E., Sheeran, B.C., Shearer, W.T., Febo, I., and Mirochnick, M. (2008). Pharmacokinetics of new 625 mg nelfinavir formulation during pregnancy and postpartum. HIV Medicine, 9(10), 875-882.
Mirochnick, M., Best, B.M., Stek, A.M., Capparelli, E., Hu, C., Burchett, S.K., Holland, D.T., Smith, E., Gaddipati, S., Read, J.S., for the PACTG 1026S Study Team (2008). Lopinavir exposure with an increased dose during pregnancy. Journal of Acquired Immune Deficiency Syndromes, 49(5), 485-491.
Weinberg, A., Dickover, R., Britto, P., Hu, C., Patterson-Bartlett, J., Kraymer, J., Gutzman, H., Shearer, W., Gelman, R., Rathore, M., McKinney, R., and the
PACTG 1021 Team (2008). Continuous improvement in the immune system of HIV-infected children on prolonged antiretroviral therapy. AIDS, 22(17),2267-2277.
Garvie, P.A., Cremeens, J., Gaur, A.H., Flynn, P.M., Belzer, M., McSherry, G., and Hu, C. for the Pediatric AIDS Clinical Trials Group 1036A Study Team (2009). Development of a directly observed therapy adherence intervention Chengcheng Hu 5 for adolescents with Human Immunodeficiency Virus-1: application of focus group methodology to inform design, feasibility and acceptability. Journal of Adolescent Health, 44(2), 124-132.
Dr. Hu has extensive research experience in both statistical methodology and collaborative clinical studies. Dr. Hu's research in statistical methodology has been motivated by problems encountered in the analysis of medical data. His current interest, arising from studies of viral and human genetics in HIV-infected patients, is to develop innovative methods to investigate the relationship between high-dimensional genetic information and longitudinal markers or survival endpoints. Other areas he has worked on include the modeling of measurement error and missing data and the strategy of design and analysis of clinical trials.