Antonio De Jesus Roman Morales

Modern Physics & Quantum Mechanics AI Trainer

Specialized in improving AI accuracy for early quantum mechanics and foundational modern physics. Expert in detecting and correcting errors in LLM-generated solutions for: Bohr-Sommerfeld quantization, wave-particle duality, Schrödinger's equation (time-independent cases), and matrix mechanics fundamentals. Combines historical physics context with mathematical rigor to train AI systems in proper applications of quantization conditions, classical-quantum correspondence, and dimensional analysis. Bridges physics history with machine learning by providing context-aware corrections that enhance both accuracy and conceptual understanding in AI physics outputs.

Key strengths: early quantum theory expertise, precision error taxonomy, corrective learning frameworks, and boundary condition verification for semiclassical systems. Proven ability to resolve discrepancies between fundamental postulates and AI-generated solutions while maintaining historical formalism.

Data Science Certificate – Coursera
(September 2024 - November 024)

• Completed comprehensive training in data science fundamentals: statistical analysis, data visualization, and machine learning
• Developed hands-on skills in Python, R, SQL, and data wrangling techniques
• Applied predictive modeling to real-world datasets through capstone projects