In this digital era, so many devices and human activities (data sources) produce big data; for example, grocery shopping behavior generates data that are useful for nutrition intervention and to form a healthy human society; driving behavior and traffic patterns generate data that are useful to enhance traffic safety; the usage behavior of household appliances produce data that are useful for energy savings and to meet environmental sustainability goals; similarly, OCT scans produce data that are useful to detect retinal diseases of a patient. These types of big data environment mean that the data may look independent until someone discovers a connection between them. The goal of my research program is to study different types of data sources (environment) and develop smart machine learning models that are domain-independent and help the discovery of such interconnected knowledge. The domain-independent models can be easily adopted by the users from multiple disciplines with minimum or no difficulties.
Funding Institutions
I am thankful to all these institutions for supporting my research. I am very fortunate to meet my collaborators who are affiliated with these institutions.
Ongoing Projects
I work on multiple research projects in collaboration with domain experts from different institutions. His current collaborators include the experts from University of Pittsburgh Medical Center, University of California Irvine, and Georgia Tech.