Research
The Questions
Three separate questions pulled me into independent research. Could a 2,500-year-old geometric method still offer insights into modern approximation problems? Could a machine learn to identify a diseased leaf the way an experienced farmer does? Could the same statistical thinking used to study structural change explain how AI is reshaping the U.S. labor market? Each question became the starting point for a new research journey.
Exploring Across Disciplines
Those questions led to three distinct projects. I wrote a research paper on the Śulba Sūtras and their relevance to modern mathematics, submitted to the Tom Rocks Maths Essay Competition. I developed Prakriti Sathi, a computer vision tool designed to help farmers diagnose plant diseases through AI. I also built a Generalized Linear Model (GLM) using IPUMS census microdata and Anthropic's AI Exposure Index to identify workers most vulnerable to employment disruption from artificial intelligence.
A Common Research Philosophy
DAlthough each project explored a different discipline—mathematics, artificial intelligence, and applied statistics—they were driven by the same instinct: to discover hidden patterns within complex real-world systems and transform those insights into solutions with meaningful practical value.
Research Outcomes
This interdisciplinary work has led to meaningful academic recognition. Two research papers have been accepted by Cureus's Student Research Journal (pending publication), while my paper on the Śulba Sūtras has been submitted to the Tom Rocks Maths Essay Competition, reflecting my continued commitment to independent, curiosity-driven research.