Blazing My Own Education Path

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My STEM path began at five, when my mother took me to an A+ math competition “for fun,” and I unexpectedly earned second place. In sixth grade, I discovered the gamma function and created a PowerPoint presentation about it. I didn’t understand all the calculus behind it, but I loved how one idea could quietly connect many others. I soon became the youngest student at my school sent to math competitions, eventually reaching ARML.

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My pursuit of mathematics continued until my sophomore year, when my pace outgrew my school’s offerings. Limbo was uncomfortable. I filled that period by searching for math content independently. Soon I discovered that I could take classes at Monroe Community College (MCC).

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Earning a degree was never my reason for enrolling at MCC; curiosity was. At fifteen, when my registration for Linear Algebra was initially rejected for being “not qualified,” I came back to ask for a chance and ultimately enrolled in the course during the summer, when requirements were more flexible.

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The accelerated summer pace required me to learn portions of calculus independently. College classes were structured differently from my high school courses, and I initially struggled, including misunderstanding expectations on the first quiz.  I adjusted quickly, identified gaps in my preparation, and earned a perfect score on the final exam. That experience clarified how deeply I value being evaluated by understanding rather than age. It then launched me into advanced mathematics courses until there were none left for me to take. By the time I graduate from high school, I will earn an associate degree in Mathematics, not because I planned it, but because curiosity does not stop at institutional boundaries.

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Math has never been something I studied to “get ahead.” I am drawn to how logic and creativity coexist within it. I devoured number theory, probability, combinatorics, and calculus not to appear advanced, but because each question led naturally to another. Alongside math, I also explored subjects such as Geologic Features of the West and Literature of the Holocaust at MCC, driven by the same desire to understand ideas in context. 

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When my school schedule limited advanced classes, I learned to study independently. In my junior year, I took eight AP exams, self-studying four and using MCC for a fifth. I earned a 5 on AP Statistics after several days of focused study. To master AP Physics 2, I took College Physics II at night through MCC and earned another 5. These experiences showed me that I learn most efficiently when driven by genuine curiosity. When studying independently, I often lose track of time designing my own problems and working through them until concepts clicked. I realized that the problems I enjoy most are not the ones with quick answers, but those that reward deep thinking, structure, and exploration without boundaries.

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Curiosity eventually led me beyond classrooms. In an engineering project supervised by a professor, I modeled the nonlinear behavior of a robotic motor for a voice-controlled windshield wiper. While discussing control systems, I realized that the curve we needed resembled a sigmoid function. I derived it independently and experimented with variations until it better matched the motor’s response. Seeing a mathematical idea reshape a physical system felt like discovering a new language.

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At Rochester Institute of Technology, I applied the same mindset to a very different problem: writing algorithms that obscure patient identities in hospital videos while preserving clinical information, later co-authoring a published review. Attending lectures alongside graduate students and researchers showed me the kind of environment where I truly belonged. Watching abstract mathematics shape technology with ethical consequences taught me that abstraction can serve human needs.

 

That realization became urgent as my grandfather endured invasive ICU procedures while a simple X-ray revealed how mathematics can make medical technology gentler, not just more powerful. I hope to study applied mathematics through modeling, inverse problems, and optimization, connecting them to machine-learning research that improves medical imaging and enables non-invasive diagnostics.

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The more I learn, the more aware I become of how much I do not yet know, and that uncertainty excites me. Curiosity has become more than an academic trait; it shapes how I learn and imagine my impact.

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