Ben Sherwood

Ben Sherwood
  • Associate Professor
  • Analytics, Information and Operations Management academic area

Contact Info

785-864-6960
Capitol Federal Hall, Room 3136
Lawrence

Personal Links

Education —

Ph.D., University of Minnesota, 2014
B.A., Macalester College, 2003

Research —

Research interests:

  • Quantile regression
  • semiparametric regression
  • high-dimensional data
  • multivariate regression
  • model selection
  • missing data

Selected Publications —

Price, B. S., & Sherwood, B. (2018). A Cluster Elastic Net for Multivariate Regression [Journal Articles]. Journal of Machine Learning Research, 18(232), 1–39.
Hong, X., Sherwood, B., Ladd-Acosta, C., Peng, S., Ji, H., Hao, K., Burd, I., Bartell, T. R., Wang, G., Tsai, H. J., Liu, X., Ji, Y., Wahl, A., Caruso, D., Lee-Parritz, A., Zuckerman, B., & Wang, X. (2018). Genome-wide DNA methylation associations with spontaneous preterm birth in US Blacks: Findings in maternal and cord blood samples [Journal Articles]. Epigenetics, 13(2), 163–172.
Wang, L., Zhou, Y., Song, R., & Sherwood, B. (2018). Quantile-optimal treatment regimes [Journal Articles]. Journal of the American Statistical Association, 113(523), 1243–1254.
Sherwood, B. (2016). Variable selection for additive partial linear quantile regression with missing covariates [Journal Articles]. Journal of Multivariate Analysis, 152, 206–223.
Sherwood, B., & Wang, L. (2016). Partially linear additive quantile regression in ultra-high dimension [Journal Articles]. Annals of Statistics, 44(1), 288–317.
Sherwood, B., Zhou, A. X., Weintraub, S., & Wang, L. (2016). Using quantile regression to create baseline norms for neuropsychological tests [Journal Articles]. Alzheimer’s & Dementia: Diagnosis & Disease Monitoring, 2(1), 12–18.