Rashika is a doctoral researcher in the MLO Lab. Her research interests span probabilistic machine learning for multi-omic data integration and foundation-model approaches for single-cell representation learning. She wrote her master thesis in the Theis Lab at Helmholtz Zentrum Munich, where she built a benchmarking pipeline for a continual learning–based autoencoder framework to construct a comparative single-cell cancer atlas. She also gained experience in single-cell data analysis at the University Medical Center Mainz and spent one and a half years as a research assistant at the German Research Centre for Artificial Intelligence (DFKI), contributing to biologically informed neural network models for cancer research.