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Incoming Caltech freshman interested in physics-informed machine learning, complex system simulation, and interpretability of AI
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Evaluated different volatility proxies for ETF forecasting with recurrent neural networks, presented my work at IEEE MIT URTC, and extended related time-series research accepted to ITISE 2026
Blogged high-level math and physics content in accessible format. Also built approachable lessons and problem sets around Calculus and Physics C content
Explored formal logic systems, Prolog, autonomous reasoning classifiers, recursive search problems, and comparative logic-learning methods. Wrote paper analyzing Explainabale (XAI) classifiers vs. traditional ML models
Nationwide book-collecting non-profit with 7,800+ books collected and 200+ volunteers; host fun book drives and fundraising tournaments
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Planning to focus on scientific machine learning, mathematical modeling, complex systems, and computational physics.
Coursework includes differential equations, multivariable calculus, AP Calculus BC, AP Statistics, DSA, AP Computer Science A, AP Physics C, and AP Macroeconomics.
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Sharing the beauty of physics+math: showcasing chaos visualizations and music sandbox and fractal lab for users to generate art
Implemented Fourier Neural Operator to solve the Darcy flow equation
Created PINN to solve heat-equation in 3D with piecewise initial conditions through custom-weighted loss function
Built course-scheduling assistant that uses LLM as semantic parser and Prolog as logic backbone for grounded and interpretable recommendations.
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