I am an M.S. student in Applied Mathematics and Statistics (Biostatistics) at Johns Hopkins University. My work sits at the intersection of statistics, machine learning, and biomedical science.

I develop statistical methods for high-dimensional biomedical data, with a focus on interpretable modeling, single-cell multi-omics, genomic mechanisms of disease, and patient risk. I am interested in tools that connect complex molecular data to clear biological and clinical insight.

My current projects span single-cell representation learning, pathway-based genetic analysis, and survival modeling in oncology clinical trials.

Tools and topics I work with: