This project explores personalized AI systems for nutrition, physical activity, and everyday health decisions. It combines causal reasoning, language models, and individual health context to generate recommendations that are adaptive, explainable, and practical.

Selected Publications

• Personalized Causal Graph Reasoning for LLMs: An Implementation for Dietary Recommendations
• PERFECT: Personalized Exercise Recommendation Framework and Architecture
• Evaluation of Large Language Models’ Accuracy and Consistency in the Registered Dietitian Exam Through Prompt Engineering and Knowledge Retrieval