I am a (final year-) Ph.D. candidate in Computer Science at the Georgia Institute of Technology, advised by Dr. Thomas Ploetz. At Georgia Tech, I am associated with the Computational Behavior Analysis and Ubiquitous Computing Lab. I am on the industry job market and am interested in exploeing opportunities that align with my skill set. I look forward to making contributions towards impactful and exciting work.

Research Interest

My research interest broadly focuses on building novel activity recognition pipelines for wearable and nearable sensing devices. During the course of my Ph.D. I have focused on developing machine learning algorithms for activity monitoring and behavior analysis. My dissertation builds pipelines for recognizing activities in smart homes, by observing data collected from residents using nearable sensors. As such I propose a ‘lifespan of a human activity recognition system in smart homes’, which includes (a) initial bootstrapping procedure - aimed at `jump-starting’ the activity recognition system in the home, with minimal supervision from the resident, without considerable wait times; (b) updating and extending the activity recognition system - aimed at improving the recognition capabilities of the initial bootstrapped system; (c) routine assessment - aimed at behavior monitoring of residents over extended periods of observation.

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