The Su Lab is particularly interested in machine learning at the interfaces between areas including:
- Real-world data such as electronic health records and American Community Survey data
- Clinical research data such as randomized controlled trials data.
- Multi-omics data such as single cell sequencing data and radiomics data.
Areas of Research Interests
- Clinical informatics and bioinformatics, electronic health records, pragmatic trials, geo-economical health disparity, single-cell sequencing, systems biology.
- Graph algorithms and artificial intelligence
- Chronical complex diseases during aging including
- Alzheimer’s diseases and cognitive health
- Cancers and immune therapies
- Chronic kidney disease
- Physical disabilities.
Highlighted Research Projects
- EMR-based pragmatic recruitment for the U.S. POINTER Alzheimer’s Disease clinical trial (Alzheimer’s Association).
- Data Coordinating Center for the U.S. POINTER Neuron-imaging Ancillary Study: a radiomics study (NIA/NIA).
- Artificial intelligence to redefine cancers in genome-phenome spaces through integrative usage of electronic health records and genomic data (AstraZeneca).
- Precision oncology for brain metastasis through incorporating multi-omics, single cell sequencing, radiomics, and clinical outcome data.
- EMR-based pragmatic clinical trial: D-CARE (PCORI).