Dr. Junhao Wen’s research endeavors focus on developing and applying artificial intelligence and machine learning (AI/ML) techniques to analyze multi-organ, multi-omics biomedical data for studying human aging and disease. His research endeavors include scrutinizing the reproducibility of AI/ML in neuroimaging research, depicting the neuroanatomical heterogeneity of brain disorders using AI/ML and imaging genetics, and embracing multiscale approaches to investigate human aging and disease. In this talk, he introduces his recent research results on multi-organ biological age gaps (BAGs) derived through machine learning. Specifically, he introduces how to use multimodal biomedical data and genetic data as instruments to analyze the associations and causal relationships between human aging and disease.