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algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical
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for cardiometabolic and liver diseases. Current therapeutic strategies largely operate at the gene level, overlooking the functional diversity generated by alternative splicing. This project addresses this critical gap
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