Sarah Samorodnitsky, PhD

Assistant Attending
Sarah Samorodnitsky

Office Phone

646-227-2383

Current Research Interest

Dr. Samorodnitsky’s research interests are in developing statistical methods for multi-omic and spatial omics datasets with the goal of identifying biomarkers of disease outcomes. Her research has spanned integrative matrix factorization methods, spatial point process models, and topological data analysis. She is also interested in novel clinical trial designs motivated by challenges in oncology research. Dr. Samorodnitsky collaborates with clinical investigators in the Bone Marrow Transplant Service and the Cell Therapy Service to address clinical and translational research questions. 

Publications

Selected peer-reviewed publications:

  1. Samorodnitsky, S., Campbell, K., Ribas, A., & Wu, M. C. (2024). A SPatial Omnibus Test (SPOT) for Spatial Proteomic Data. Bioinformatics, 40(7), btae425.
  2. Samorodnitsky, S., Campbell, K., Little, A., Ling, W., Zhao, N., Chen, Y. C., & Wu, M. C. (2024). Detecting Clinically Relevant Topological Structures in Multiplexed Spatial Proteomics Imaging Using TopKAT. bioRxiv.
  3. Samorodnitsky, S., Othus, M., LeBlanc, M., & Wu, M. C. (2024). Reverse Selection Designs for Accommodating Multiple Control Arms. Clinical Cancer Research, 30(24), 5535-5539.
  4. Samorodnitsky, S., & Wu, M. C. (2024). Statistical Analysis of Multiple Regions-of-Interest in Multiplexed Spatial Proteomics Data. Briefings in Bioinformatics, 25(6), bbae522.
  5. Samorodnitsky, S., Wendt, C. H., & Lock, E. F. (2024). Bayesian Simultaneous Factorization and Prediction Using Multi-Omic Data. Computational Statistics & Data Analysis, 197, 1079