Academic Clinical Affairs, Ofc
Twin Cities
This group's primary research interest is the application of statistical modeling, machine learning, and causal analysis methods in the field of biology and medicine. Specifically, approaches include: devising and implementing new causal discovery methods that are specifically tailored to the characteristics of biomedical data; benchmarking novel and existing causal discovery and predictive modeling methods in order to evaluate their efficacy on biomedical data; and designing analytical experiments to discover critical contributing factors to pathologies and diseases from multimodality high-dimensional high-volume data to aid the development of diagnostic technologies and identification of potential treatment targets.