ResearchGate Preprint, 2026
This survey reframes emotionally aware AI around evaluation and safety, analyzing existing generative models, datasets, and benchmarks for evaluating emotional intelligence in affective computing systems.
Recommended citation: Nicole Hao. (2026). "Emotionally Aware AI Models: An Evaluation-and Safety-Centric Survey." ResearchGate Preprint.
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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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Work In Progress, 2025
This work develops a multimodal STEM lecture video dataset and annotation framework for training and evaluating vision-language models on educational understanding.
Recommended citation: Nicole Hao. (2025). "InkSight: A Multimodal STEM Lecture Video Dataset and Data Labeling Tool." Work In Progress.
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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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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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