Institute: Boston University School of Medicine
Biography
Assistant Professor in systems immunology, applying machine learning to understand how vaccines work, specifically focused on human immunology and data-driven research. Co-developer of SIMON, an open source platform for the application of machine learning to biological and clinical data.
My research focus is to understand the signature of protective immunity in humans. The hallmark of protective immunity is the ability of the immune system to mount an effective response to a given pathogen. The immune system comprises multiple cell types that work together to develop an effective response. Which of myriad cell types are important in a particular response, however, is not well understood. In my research, I apply systems-level analysis to measure all the aspects of an immune response. By applying systems-level analysis, such as mass cytometry, systems serology and transcriptomics, hundreds of parameters are captured, including gene expression, frequencies and functionality of cells and molecules in the immune system, during an infection or vaccination to reveal which cell types are important in a particular response. Using SIMON, our recently developed approach for machine learning, I identify patterns and extract knowledge from multidimensional data to guide data-driven research. Using machine learning to extract meaningful patterns in data can reveal immune cells and correlates of protection that other approaches may miss. SIMON successfully identified immune signature involved in mounting an effective antibody response to seasonal influenza vaccine.
Key Publications
A list of publications can be found here.
Web Links of Interest