I am a computational research fellow specializing in the application of machine learning to immunology and cancer research. My Ph.D. work focused on developing advanced algorithms for optimizing donor-recipient matching in stem cell transplant, with an emphasis on HLA-driven matching strategies. Currently, my research focuses on developing predictive models of treatment response and identifying new biomarkers for CAR T-cell therapy and stem cell transplant, using time-series and multimodal data.
Awards/Grants:
- Best Research Paper of 2023, Human Immunology journal
- VATAT Scholarship for Doctoral Students in Data Science (2022)
- The Bar-Ilan Postdoctoral Scholarship for Women (2024)
Israeli, S., & Louzoun, Y. (2024). Single-residue linear and conformational B cell epitopes prediction using random and ESM-2 based projections. Briefings in Bioinformatics, 25(2), bbae084.
Israeli, S., Gragert, L., Madbouly, A., Bashyal, P., Schneider, J., Maiers, M., & Louzoun, Y. (2023). Combined imputation of HLA genotype and self-identified race leads to better donor-recipient matching. Human Immunology, 110721.
Israeli, S., Krakow, E. F., Maiers, M., Summers, C., & Louzoun, Y. (2023). Trans-population graph-based coverage optimization of allogeneic cellular therapy. Frontiers in Immunology, 14, 1069749.
Israeli, S., Gragert, L., Maiers, M., & Louzoun, Y. (2021). HLA haplotype frequency estimation for heterogeneous populations using a graph-based imputation algorithm. Human Immunology, 82(10), 746-757.