AI Mathematical Reasoning Evaluator
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Developed rigorous multi-step calculus and algebra problems to evaluate the reasoning capabilities of Large Language Models (LLMs). Applied structured scoring criteria to measure AI-generated solutions for accuracy, logical structure, and constraint alignment. Used Python libraries to validate outputs, detect errors, and document findings in detail.
• Designed and evaluated mathematical test data specifically for AI assessment.
• Implemented a comprehensive validation approach using NumPy and SciPy.
• Defined and maintained detailed scoring rubrics for AI outputs.
• Documented scientific edge cases and logical boundary conditions to enhance AI evaluation integrity.
Developed rigorous multi-step calculus and algebra problems to evaluate the reasoning capabilities of Large Language Models (LLMs). Applied structured scoring criteria to measure AI-generated solutions for accuracy, logical structure, and constraint alignment. Used Python libraries to validate outputs, detect errors, and document findings in detail. • Designed and evaluated mathematical test data specifically for AI assessment. • Implemented a comprehensive validation approach using NumPy and SciPy. • Defined and maintained detailed scoring rubrics for AI outputs. • Documented scientific edge cases and logical boundary conditions to enhance AI evaluation integrity.
2021 - Present