Description of Research Expertise

My research focuses on decoding the functional impacts of adaptive immune receptors using computational, genomic and experimental approaches. We are a hybrid lab with both wet and dry components. We have three major ongoing directions: First, the adaptive immune system is sensitive to early disease cues, such as cancer, providing a unique opportunity for detection of early-stage cancers. My lab is dedicated to developing novel computational tools to extract useful information from the TCR or BCR repertoires to achieve immune-based early cancer detection. Second, we investigate the complicated interactions between tumor and the immune system through novel methodology development. In a recent work, we observed that cancer cells can 'hijack' mitochondria from nearby T cells, thus causing T cell metabolic dysfunction. We have introduced a novel computational tool to investigate this process in the human cancers, and we are actively investigating potential targets to block this process. Third, autologous antibodies produced by tumor-infiltrating B/plasma cells provide valuable information in the spontaneous anti-tumor immune response. We develop novel deep neural network methods to infer the antibody-antigen interactions by using the BCR sequences identified in the tumor microenvironment, aiming to find novel tumor antigen targets as well as high-affinity antibodies for effective cancer immunotherapies.