STEM Data Analysis & Annotation (Independent)
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Analyzed and labeled complex physics and STEM datasets for AI model training and evaluation. Developed structured, multi-step reasoning chains across electromagnetism, mechanics, and quantum physics problems. Validated computational outputs against physical laws and theoretical expectations.
• Utilized large language models to generate and verify technical content.
• Ensured labeled datasets supported effective model learning and generalization.
• Implemented rigorous validation protocols for improved dataset accuracy.
• Contributed expertise across diverse physics domains for AI training.
Analyzed and labeled complex physics and STEM datasets for AI model training and evaluation. Developed structured, multi-step reasoning chains across electromagnetism, mechanics, and quantum physics problems. Validated computational outputs against physical laws and theoretical expectations. • Utilized large language models to generate and verify technical content. • Ensured labeled datasets supported effective model learning and generalization. • Implemented rigorous validation protocols for improved dataset accuracy. • Contributed expertise across diverse physics domains for AI training.
2023 - Present