Research

Research Interests

My research focuses on developing computational methods for single-cell multiomics analysis, with an emphasis on improving key analytical tasks in single-cell RNA sequencing (scRNA-seq). I am particularly interested in advancing algorithms for analyzing cellular heterogeneity, modeling gene regulatory networks, and integrating multiomic datasets to uncover biologically meaningful patterns. Recently, my work has expanded to include deep learning approaches for in silico gene perturbation prediction, as well as the application of large-scale pretrained models for understanding transcriptional programs.

In addition to method development, I apply state-of-the-art AI/ML tools to investigate complex diseases, including Duchenne Muscular Dystrophy and various cancers. By bridging computational innovation with biomedical applications, my work aims to improve our understanding of cellular behavior and contribute to the development of precision medicine strategies.