About me

I am an AI Research Scientist and ML Engineer specializing in Large Language Models (LLMs), Generative AI, NLP, and Agentic AI Systems. I currently serve as a founding ML engineer at 4minds.ai, where I build enterprise private LLM and ML solutions end-to-end — spanning data preparation, data engineering, model pretraining and post-training, fine-tuning, knowledge graph construction, retrieval-augmented generation, and agentic systems. At 4minds, we deliver the full model lifecycle so enterprises own their intelligence, not just access it.

I hold a PhD in Artificial Intelligence and Machine Learning from the University of Texas at Arlington, where I conducted research under the supervision of Dr. Jeff Lei. My doctoral work focused on improving the reliability and interpretability of ML systems through Explainable AI (XAI), robustness testing, and automated model debugging — producing practical frameworks for analyzing model failures, mitigating bias, and enhancing performance stability under real-world conditions.

My technical expertise spans data preparation and feature engineering, deep learning, transformer architectures, LLM pretraining and fine-tuning, knowledge graph construction, retrieval-augmented generation (RAG), multimodal AI, and multi-agent orchestration. I have hands-on experience designing and training models end-to-end — from data curation and preparation through custom pretraining, embedding-based retrieval with vector databases, and advanced fine-tuning techniques for domain-specific LLMs.

I am passionate about advancing the trustworthiness and responsible deployment of AI at scale — bridging frontier research with production engineering to deliver AI systems that are robust, interpretable, and enterprise-ready.