Research Expertise and Interest
machine learning, trustworthy data science and AI, interdisciplinary research in biomedicine, neuroscience, and climate science.
Research Description
Bin Yu is the Class of 1936 Second Chair in the College of Letters and Science and a Chancellor's distinguished professor in the Department of Statistics, EECS and Center for Computational Biology. She is also a senior advisor at the Simons Institute for Theory of Computing. Her current research has focused on the practice and theory of machine learning and solving interdisciplinary data problems in neuroscience, genomics, and precision medicine (e.g. in ER and cardiology). The Yu group has developed machine learning algorithms such as next-generation and interpretable tree-based methods (e.g. iterative random forests (iRF), fast and greedy sums of trees (FIGS), HS, and MDI+), stability-driven NMF, and adaptive wavelet distillation (AWD) from deep learning models.