Research Direction：
Machine learning
Visual information acquisition and processing
Research Direction：
Research interests include optimization theory and methods for networked cyber-physical energy systems with particular contribution to ordinal optimization, event-driven optimization and the applications.
Research Direction：
1. Genetic sequencing data analysis
2. Genomic deep learning
3. Medical knowledge graph construction
4. Intelligent analysis of medical images
Research Direction：
Computational energy intelligence, Bayesian optimization, Battery management system, Data-driven fault monitoring.