Network-Based Machine Learning for Biomedical Big Data
Ali Shojaie
June 1, 2022, Wednesday, 3:00 PM - 4:00 PM EDT
Machine learning and artificial intelligence (ML/AI) tools are used broadly across biomedical sciences but seldom provide insights into mechanisms underlying disease initiation and progression. In this talk, we will discuss machine learning approaches based on networks that aim to discern underlying biological mechanisms, as well as their applications in diverse biomedical studies, including studies based on omics and neuroimaging data.
Ali Shojaie is professor and associate chair of biostatistics at the University of Washington School of Public Health. Shojaie's research focuses on developing statistical machine learning and network analysis methods and applying them to analyze biological systems. He has made important contributions to the development of high-dimensional graphical models, analysis of biological networks, integration of biological knowledge into analysis of omics data, and analysis of neuroimaging data. Shojaie is also the founding director of the Summer Institute in Statistics for Big Data (SISBID) and teaches multiple short and regular courses on applications of machine learning and network-based methods for the analysis of biomedical big data.