Azim Rezaei

I am a Machine Learning researcher and a PhD Candidate at Texas A&M University, Corpus Christi, with a passion for developing robust and privacy-preserving artificial intelligence. My work exists at the intersection of Reinforcement Learning (RL), Large Language Models (LLMs), and Generative AI. I specialize in engineering novel frameworks that solve real-world challenges, from building Graph Neural Network (GNN) and Transformer-based models for complex forecasting to pioneering vision-to-text transformations that enhance security in intelligent systems.

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What I Do

I focus on the design, implementation, and deployment of advanced machine learning models. My key areas of expertise include:

1. Generative AI & LLMs: Developing frameworks powered by Large Language Models, including the integration of Retrieval-Augmented Generation (RAG) and Mixture of Experts (MoE) models into real-time systems.
2. Reinforcement Learning: Implementing feedback-driven RL to optimize complex systems, such as privacy-preserving visual systems for intelligent transportation.
3. Multi-Modal & Time-Series Forecasting: Building and fine-tuning Graph Neural Network (GNN) and Transformer-based models for multi-modal spatio-temporal network traffic forecasting.
4. End-to-End ML Deployment: Engineering complete CI/CD pipelines for machine learning workflows, from data ingestion and model training to scalable cloud deployment using tools like Docker, AWS Lambda, and Amazon SageMaker.