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My research interest is to understand how nutritional metabolomics can help promote long-term health across the lifespan. Multiomics data with dietary information followed by a multivariate machine learning technique is more powerful in detecting early changes in physiological processes than the limited set of individual biomarkers of chronic diseases. It is especially critical in the early detection and prevention of neurocognitive diseases, where visible symptoms manifest decades after their initiation, such as Alzheimer’s disease. My long-term academic goal is to utilize multiomics-based tools to help identify the optimal diet(s) for prolonged health span using epidemiological, interventional and mechanistic data and help address the present challenges in translating large multiomics data to meaningful practical use to accomplish the goal of precision nutrition.