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My research is data analytics and machine learning intersecting with systems or domains having complex data structures, such as large volume, high dimensionality, heterogeneity, multi-source, multi-level, and multi-task. My methodological development also emphasizes integration of data-driven analytics with domain knowledge.


Specifically, I have been working on the following areas:

§  Health care analytics

§  Integrative modeling and analysis of medical imaging, genomics, and clinical data toward personalized medicine. Focused diseases include solid tumor cancer and brain diseases (e.g., the Alzheimer’s disease, migraine).

§  Health care system informatics and data analytics for improving quality and process efficiency

Collaborators: Mayo Clinic, UCSD Chemistry and Biochemistry, Banner Alzheimer's Institute, University Medical Center Mainz (Germany), ASU School of Nursing and Health Innovation

Funding support: NIH, Mayo Clinic, Arizona State, ASU Rising Star Grant


§  Network analytics

§  Machine learning methods for network big data

§  Monitoring, anomaly detection, and prognostics in large communication networks

Collaborators: U.S. Army Electronic Proving Ground (EPG), ASU Security and Defense Systems Initiative

Funding support: U.S. Army EPG, Army Research Office


§  Quality and reliability engineering

§  Transfer learning based process modeling and control

§  Multi-sensor fusion and sensing data uncertainty analysis

§  Reliability modeling and prognostics of hierarchical systems

Collaborators: Manufacturing industries

Funding support: NSF, Intel