Michael Yu is a Research Assistant Professor at the Toyota Technological Institute at Chicago. He received a dual B.S. in mathematics and computer science in 2010 and an M.Eng. in computer science in 2011 from MIT. Prior to coming to Chicago, Michael completed his Ph.D. in Bioinformatics and Systems Biology from the University of California San Diego in 2017 and continued as a postdoc in 2018.
Michael’s research focuses on computational and integrative approaches for systems biology. He has designed methods that integrate heterogeneous ‘omics datasets to learn the multi-scale organization of a biological system. For example, he has modeled the hierarchy of components and pathways in a yeast cell and used this structure to explain millions of genotype-phenotype relations. He is a proponent of “visible” machine learning models (as opposed to black-boxes) that not only make accurate predictions but also provide hypotheses about biological mechanisms. Michael is broadly interested in unraveling the network of interactions within and between the human microbiome, the immune system, and disease development. As part of this effort, he is investigating the multi-scale organization of each of these biological systems. In particular, how is the microbiome structured from genes and molecular pathways to cells and microbial subcommunities? What are the steps regulating differentiation and signaling in the immune system? What are the mutational patterns and selective pressures that drive cancer evolution? To answer these questions, he is analyzing heterogeneous data sources– including large sequencing efforts in clinical cohorts, functional screens in cell culture and mouse models, and genomic annotations in knowledge bases.
Besides research, Michael enjoys cooking and long-distance running!