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My research focus has been on learning robust machine learning models from small pool of complete instances. A practical application of this has been in finding potential recruits given the availability of a small number of patients with complete information from a clinical study or survey data. This has been applied to real world medical problems like Parkinson’s, Alzheimer’s disease,rare disease and Post partum depression where a small number of patients with the complete feature set remains available and the goal is to identify potential recruits having easily available partial feature set for better disease prediction. My big goal is to build an intelligent decision support agent that can assist physicians in making better healthcare decisions.