I began my journey into research in 10th grade (2020). Covid-19 was the style du jour, masks were all the rage, and I was enrolling in a class at my school called Science Research. This class was meant to guide students, helping them reach out to experienced mentors in academia and industry. Initially, I was tasked with finding a broad area of study, for example, cancer, in which I could later specify and find a niche that fit me precisely. Even at this early stage, however, I was torn. I had always loved mathematics, but I also adored biology and any topics which had to do with the human body, and I was struggling with finding a topic that neatly tied the two together. It was on a random winter day during the weekend, when I went to a diner with my father for breakfast … There, they had a TV set playing the news, where the latest projected Covid-19 numbers were being displayed. It was at that point my father suggested to me that I should research disease models. There was heavy mathematics used in the creation and analysis of these models, while a strong understanding of diseases and disease epidemiology was required to accurately understand and implement disease models. After some basic investigation, I was smitten … For the rest of the year, I became engrossed in epidemiology, learning about compartmental and agent-based models, disease routes of infection and interventions, and quite excitingly, following the most up-to-date research on Covid-19. When the summer rolled around, I eagerly sent emails to research groups working with disease models. A group at NYU Langone’s Translational Research Department wrote back, and I eagerly began interning at their lab. They worked more on HIV than Covid-19, however, so for the first summer, I investigated their HIV model, EMOD, and learned how to interface with it. I also began learning about HIV itself and applied that knowledge to understanding EMOD. My mentor had also mentioned to me that EMOD, their model, was unable to allocate money to different disease treatment programs. Including this capability was their next goal, and so I also began studying optimization algorithms, specifically those used for more complex problems.

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