MSc Data Science candidate specializing in machine learning, health informatics, and predictive analytics — bridging rigorous research with impactful real-world applications.
I turn complex datasets into meaningful insight — whether that's predicting bus seat sales across 14 routes, modeling menstrual cycle regularity across 1,660 longitudinal records, or building dashboards that reveal hidden patterns in revenue data.
My work lives at the intersection of human health, behavioral data, and machine learning. I'm particularly drawn to personal informatics: systems that help people understand themselves better through their own data.
Currently completing my MSc at Amrita Vishwa Vidyapeetham, with a minor in Logistics & Supply Chain Management — and preparing my first research manuscript for journal submission.
A pioneering framework that integrates menstrual cycle data with personal productivity scheduling — addressing a gap in personal informatics research that typically ignores biological rhythms in task management.