Ching-Tsung (Deron) Tsai is a master student in Biostatistics at NYU. He’s interested in applying rigorous quantitative methods to real-world topics with his most recent focus on supervised machine-learning-based disease prediction. Regardless that misclassification errors may have unequal costs, traditional classifiers are optimal with respect to minimizing the overall error rate. To address the need for asymmetric error control, he’s currently implementing the multi-class Neyman-Pearson (NP) algorithm on popular machine learning classification models for practical applications.