I am a Ph.D. student in the School of Electrical and Computer Enginnering at Georgia Institute of Technology. I am advised by Prof. James Rehg. I am broadly interested in the field of machine learning for healthcare and mobile health.
My research involves developing methods for improving the effectiveness of mobile health interventions using machine learning and signal processing tools. My past projects involve (1) Detecting the clinical state of heart failure from Ballistocardiography signals collected in a home environment. (2) Detecting sleep stages in mice using novel electric field sensors placed on the walls of the home-cage. (3) Prediction of glaucoma progression using spatiotemporal data modeled using a Continuous-time Hidden Markov Model (CT-HMM).
I am currently working on the problem of analyzing and modeling user engagement in mobile health. I am specifically working on promt-level ecological momentary assessment (EMA) compliance in mobile health studies, and developing predictive tools for this problem.
Outside of research, I enjoy being outdoors - hiking, biking, and running. I enjoy cooking, theatre performances, and am proficient in Indian classical music.
School of Electrical and Computer Engineering
Georgia Institute of Technology