About me
Duy is a computational biologist specializing in the application of machine learning and deep learning to genomics. His research centers on single-cell and spatial transcriptomics, with a particular emphasis on developing computational methods that uncover the molecular and cellular mechanisms underlying human health and disease.
Duy applies generative models and deep representation learning to disentangle biological signals from technical variation, enabling robust identification of invariant cellular features across diverse conditions. He has contributed to the construction of high-resolution cellular atlases and integrative models of gene regulation, advancing the understanding of tissue organization, immune response, and disease progression.
Through a combination of algorithmic innovation and collaborative science, his work bridges data science and biology, offering new insights into complex cellular ecosystems. His long-term goal is to develop predictive frameworks that connect molecular profiles with physiological outcomes, ultimately informing diagnostic strategies and therapeutic development.