Department of Computer Science and Engineering
PhD, Computer Science, University of Colorado Boulder, 2012
Model host-microbiome interactions; applied methods to find patterns in microbial communities that predict and diagnose human diseases.
Dan Knights is a computational microbiologist whose research uses data mining and machine learning to study the microbiome in human disease. He teaches courses on computational techniques used to analyze biological data generated by genome sequencing, proteomics, cell-wide measurements of gene expression changes. Outside of work, Dan is also well-known in the field of speedcubing.