Yuyue Chen, ’21

How can one make an aggregated buying/selling decision based on recommendations from multiple stock analysts?

Data-driven analytics and decision-making have been essential for numerous applications in our society. To transform the data into a source of rich intelligence and support decision-making, data-driven analytics often need to aggregate intelligence from multiple sources and disaggregate signals into significant constituents. Though many existing approaches perform these two tasks respectively, there are few attempts to study them with a holistic view. My research exploits the intrinsic connections between intelligence aggregation and signal disaggregation by developing novel models to capture and leverage various types of inter-correlations in the data from complex systems.

Although I used specific data sets to implement my research framework, my models for aggregation and disaggregation of information are applicable in different fields such as finance, production management, household utility analysis, marketing and so on. In general, my research models can address the challenges in aggregating intelligence from multiple sources as well as disaggregating signals for complex systems.