His general research interest involves statistical methods for data mining, machine learning, survival analysis, Bayesian methodology, and their applications in bioinformatics, finance, medical and healthcare data. His developed models and tools are successfully applied to several types of cancer data for detecting the stage of the cancer, type of cancer, and survival time of the patients. They are also used in predicting the composition of a material based on near infrared spectroscopy like plasma, petroleum, and food content. Prof. Chakraborty is awarded with multiple NSF and NIH grants for his research. Prof. Chakraborty is currently working on multi-platform multi-omcis data integration based on statistical models.