Nicole Hao

Nicole Hao

AI engineer, CS/math researcher, and technical founder. Passionate about turning research into scalable, everyday tools.

Publications

You can also find my articles on my Google Scholar profile.

Preprints

Quantitative Sobolev Approximation Bounds for Neural Operators with Empirical Validation on Burgers’ Equation

Machine Learning: Science and Technology (In Submission), 2025

This paper derives a complexity-error scaling law in Sobolev norms and validates it empirically with Fourier Neural Operators.

Recommended citation: Nicole Hao. (2025). "Quantitative Sobolev Approximation Bounds for Neural Operators with Empirical Validation on Burgers Equation." In submission to Mach. Learn.: Sci. DOI: 10.13140/RG.2.2.32739.62248
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Journal Articles

Detecting and Classifying Solar Flares in High-Resolution Solar Spectra using Supervised Machine Learning

Published in The Astrophysical Journal, 2024

This paper presents a novel, standardized procedure for classifying solar flares using supervised machine learning, with implications for both solar physics and exoplanet research.

Recommended citation: Nicole Hao, Laura Flagg, Ray Jayawardhana. (2024). "Detecting and Classifying Solar Flares in High-Resolution Solar Spectra using Supervised Machine Learning." The Astrophysical Journal.
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Conference Papers

Option Pricing with Stochastic Volatility, Equity Premium, and Interest Rates

Published in The Joint Mathematics Meeting, 2024

This paper formulates and derives new parabolic partial differential equations using stochastic differential equations, replicating portfolio theory, and risk-neutral pricing to model time-varying volatility, equity premium, and interest rates.

Recommended citation: Nicole Hao, Echo Li, Diep Luong-Le. (2024). "Option Pricing with Stochastic Volatility, Equity Premium, and Interest Rates." The Joint Mathematics Meeting.
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