Summary
The big data analytics research in IMCL focuses on multi-source cross-domain big data fusion and big data analytics for multi-stage complex systems. Our mission is to contribute real value in smart logistics, smart health, smart education, and smart food safety:
- Multi-source Cross-domain Big Data Fusion: Because of the dynamics, uncertainty, heterogeneity, and complexity of big data, fusing multi-source and cross-domain data to obtain useful and interpretable information is a grand challenge in big data analytics. We develop novel data-driven approaches for effectively fusing multi-source and cross-domain big data at both the feature level and model level.
- Big Data Analytics for Multi-stage Complex Systems: Traditional big data analytics treats the system under study as an atomic entity with all its data directly available for analysis. However, most systems under study are complex, consisting of separable but interdependent subsystems that are difficult to handle with existing single-stage methods. We develop new methodologies for multi-stage big data analytics on complex systems that address the challenges brought up by the diverse requirements, high dependency, and correlated objectives of the subsystems.
