Dr. Su is interested in biomedical informatics that incorporates electronic health records, graph-based machine learning, big data integration and mining, and computational models:
- to identify clinical phenotypic traits of patient subgroups that demonstrate different risk factors, disease development patterns, and treatment responses;
- to understand the underlying mechanisms of such subgroups from perspective of the dynamics of complex biosystems; and
- to apply actionable knowledge in precision medicine and clinical decision-making.
He currently focuses on three closely related directions: biomedical informatics for precision medicines, graph theory in machine learning and biomedical big data mining, and systems biology of stem cell driven biosystems. Dr. Su is interested in 5 closely correlated chronic complex diseases: diabetes, kidney diseases, cancers, cardiovascular diseases, and Alzheimer's/dementia.