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Cliburn’s quantitative science group is interested in the development of computational, mathematical, and statistical models and software tools for monitoring and profiling the immune response, especially in the context of clinical research. They are particularly interested in the statistics of single cell dynamics as measured with single cell PCR, multi-parameter flow cytometry, and high content imaging. Their approach makes heavy use of Bayesian non-parametric methods (collaboration with Mike West’s group) on extremely large data sets as well as the use of massively parallel computation with GPUs to tackle previously impractical problems. They also collaborate closely with the Duke Center for AIDS Research Flow Cytometry Core, the Duke Translational Research Institute Immune Monitoring Core, and several clinical research groups at Duke interested in the immune response to HIV infection, lung transplantation, and melanoma regional therapy. Their software development is mostly in Python, with wrapped C/C++ code for computationally intensive routines and GPU kernels.