The vast landscape of the human genome hosts elements that orchestrate the dynamics of proteins in every human cell, establishes cell identity, and safeguards the defense mechanisms. These elements, known as gene regulatory elements, are encrypted in a different genomic language known as the second language of genomes. As this second language of genomes remains largely unknown, my research mainly focuses on developing novel artificial intelligence methods to understand the genomic encryption of gene regulatory elements and studying the evolution of the gene regulatory code in eukaryotes. Specifically, I'm interested in prioritizing the regulatory variants of non-coding genomic regions to identify the linkage between sequence variation of the regulatory elements and disease, and that between regulatory elements sequence variation and phenotypic divergence across species. In the context of cancer, I'm interested in developing mechanism-based models to identify functional, and potentially causative ‘driver’ regulatory mutations in cancer.