MohammadReza Mohammadi

Developed a predictive neural network for healthcare (92% accuracy), deployed with Streamlit, Docker, AWS, PostgreSQL, cutting processing time by 30%. Built a DCGAN for synthetic data, improving quality by 20% and training efficiency by 15%, boosting model accuracy by 12%. Implemented LLM-based classification (96% accuracy), reducing manual effort by 50% and increasing speed by 35%. Optimized ML models, increasing accuracy by 18% and cutting cloud costs by $50K annually.

Built a travel time prediction model, cutting errors by 26%, boosting accuracy by 18%, and raising satisfaction by 15%. Optimized ML models (XGBoost, RF), achieving 92% accuracy and reducing errors by 30%. Applied Bayesian inference for market trends, increasing profit by 12% and cutting risk by 20%. Developed neural networks, improving efficiency by 25% and saving $150K annually. Designed a CNN (95% accuracy), cutting training time by 40% and p processing by 35%. Deployed ML models on AWS,