My research interests include computational biology and bioinformatics as they apply to cancer genomics and radiation oncology. My doctoral work focused on developing structural variation discovery tools using next-generation sequencing data, including SVseq 1 & 2. I also worked on algorithmic problems in haplotype inference, recombination, rare variants, etc. My postdoctoral work focused on developing algorithms analyzing whole transcriptome sequencing data to discover RNA specific aberrations and their applications in cancers. We designed and implemented the state-of-the-art gene fusion discovery tool, INTEGRATE, leading to his discoveries of novel biomarkers in breast cancer, liver cancer, leukemia, etc. We implemented the first tool in cancer immunology, INTEGRATE-Neo, to predict neo-antigens from tumor specific gene fusion peptides. We discovered a single-gene biomarker, lncRNA PCAT-14, in prostate cancer metastasis, and novel mid-sized small RNAs in acute myeloid leukemia. I am currently working on creating and integrating advanced computational approaches using high-throughput sequencing data and imaging data into the development of novel diagnostic, prognostic, and therapeutic strategies in cancer.