Jeremy Rubin
Dr. Jeremy Rubin received bachelor's degrees in Statistics and Mathematics from the University of Maryland, Baltimore County and a PhD in Biostatistics from the University of Pennsylvania. His research group, the MACHine leArning for bioMarker discovery and Prediction (MACHAMP) Lab (https://sites.google.com/umd.edu/jeremyrubin/research-areas-projects-and-lab-members), focuses on developing and applying machine learning methods for biomarker discovery and prediction of patient outcomes. When he’s not teaching or doing research, you can probably find Dr. Rubin making a pun, having coffee, playing badminton, watching or sometimes even performing stand-up comedy.
Contact
Departments/Units
Areas of Interest
Application: Biomedical imaging (including renal histopathology, neuroimaging, and vascular imaging), electronic health records (including transplant registry data)
Methodology: Unsupervised clustering, high-dimensional regression (especially lasso-based approaches), random forest, XGBoost, ensemble learning, feature/variable selection, data harmonization
University of Pennsylvania Philadelphia, PA
- Ph.D., Biostatistics April 2025
- M.S., Biostatistics May 2022
University of Maryland, Baltimore County Baltimore, MD
- B.S., Statistics and Mathematics May 2020
J. Rubin, F. Fan, L. Barisoni, A. R. Janowczyk, J. Zee (2026). Analysis of Correlated Imaging Features using Scalar-on-matrix Regression. Statistical Analysis and Data Mining, 19 (2).
J. Rubin, F. Fan, L. Barisoni, A. Janowcyzk, J. Zee (2026). Novel Scalar-on-matrix Regression for Unbalanced Feature Matrices. Statistics in Biosciences, 18 192-213.
V. S. Potluri, J. Rubin, J. Zee, S. J. Ratcliffe, M. O. Harhay, P. L. Abt, E. A. Vail, C. R. Parikh, R. D. Bloom, A. Gasparini, M. Crowther, D. S. Goldberg, P. P. Reese (2026). Assessing the Quality of Deceased Donor Kidneys through Post-Transplant Survival Prediction Algorithms. American Journal of Kidney Diseases, 87 (1).
J. Rubin, Q. Cao, Y. Sakai, N. Arnett, H. Q. Phi, A. C. Hu, B. L. Cucchiara, D. Bos, L. Saba, E. Johannson, J. Zee, J. W. Song (2025). Association of Carotid Plaque Calcification Attenuation With Intraplaque Hemorrhage Volume: 3D-Segmentation Analysis. Journal of Neuroimaging, 35 (4).
F. Fan, Q. Liu, J. Zee, T. Ozeki, D. Demeke, Y. Yang, A. B. Farris, B. Wang, L. Mariani, K. Lafata, J. Rubin, Y. Chen, L. Holzman, J. B. Hodgin, A. Madabhushi, L. Barisoni, A. Janowczyk. Clinical relevance of computationally derived tubular features and their spatial relationships with the interstitial microenvironment in minimal change disease/focal segmental glomerulosclerosis. Kidney International, 108 (2) 293-309.
Y. Chen, J. Zee, A. Janowczyk, J. Rubin, P. Toro, K. Lafata, L. Mariani, L. Holzman, J. Hodgins, A. Madabhushi, L. Barisoni (2023). Clinical Relevance of Computationally Derived Attributes of Peritubular Capillaries from Kidney Biopsies. Kidney360, 4(5) 648-658.
J. Rubin, L. Mariani, A. Smith, J. Zee (2022). Ridge regression for functional form Identification of continuous Predictors of Patient-Reported Outcomes in Glomerular Disease. Glomerular Diseases, 3 47-55.