I am a Ph.D. candidate in the Department of Computer Science at Dartmouth College, working with Prof. David Kotz in the domain of mHealth sensing and intervention. I am also affiliated with the Center of Technology and Behavioral Health (CTBH) at Dartmouth.
My research interest broadly focuses on developing novel sensing and intervention systems for smartphones and wearable devices. Specifically, I work on exploring and advancing the complete ``lifecycle’’ of mental- and behavioral-health sensing and intervention, which includes (a) accurately sensing and detecting a mental or behavioral health condition, like stress and opioid use; (b) after detecting a particular condition, determining the right time to deliver the intervention or support, such that the user is most likely to be receptive to the interventions provided; and (c) choosing the best intervention delivery mechanism and modality to ensure just-in-time delivery and reachability.
I obtained my B.Tech. in Computer Science & Engineering with a Minor in Mathematics from Shiv Nadar University, India (2015). I spent the summer of 2018 as a Research Intern in the Computational Health Behavior & Decision Science team at IBM Research.
(January, 2021) Our paper on understanding how drivers interact with in-vehicle well-being interventions has been accepted at IMWUT, and will be presented at UbiComp 2021. Preprint is available here.
(December, 2020) Our paper on evaluating the reproducibility of stress-detection models has been published at IMWUT, and will be presented at UbiComp 2021.
(June, 2020) Our paper, Detection of Artifacts in Ambulatory Electrodermal Activity Data, has been accepted at IMWUT, and will be presented at UbiComp 2020.
(March, 2020) Our paper on the effectiveness of physical activity interventions has been published in Annals of Behavioral Medicine.
(February, 2020) Gave a talk on Clinical Trajectories of Individuals with Opioid Use Disorder at ETH Zurich. Read more about this project here.
(February, 2020) Gave a talk on Detecting Stress from Physiological Signals at ETH Zurich.