Our research falls under the general category of industrial data science, or engineering system informatics. Two focus areas of engineering applications of our lab are: wind energy and material & manufacturing. Industrial data science research tackles engineering system problems with a full mind of the rapidly growing capability for data collection, the same capability creating the era of big data. There is a pressing need to develop sophisticated statistical and computational methodologies that enable and assist
- the handling of the rich data streams communicated by complex engineering systems,
- the extraction of pertinent knowledge about the environmental and operational dynamics driving these systems, and
- the exploitation of the acquired knowledge for enhanced design, analysis, and control.
Unlike purely data-driven approaches, our research emphasizes the integration of engineering system modeling and data science methods, thereby enhancing the capability of engineering decision making.
Additional Materials:
1. Ph.D. student, Aziz Ezzat, explains our wind energy research https://youtu.be/rKQCIq2qsm4
2. An article about data science for wind energy https://tees.tamu.edu/news/2018/09/27/yu-ding-brings-data-science-to-wind-energy/
3. A book about data science for wind energy https://aml.engr.tamu.edu/book-dswe/.