Master of Science in Computer Science
University of Virginia
Specialized in artificial intelligence, machine learning, and large language model applications — pairing rigorous coursework with hands-on research building production-grade AI systems.
Coursework
Skills Developed
Achievements
- Graduated with a 3.94 / 4.00 GPA across rigorous AI coursework.
- Designed an LLM-vs-LLM fault-localization framework using Gemma-3 12B with PEFT and QLoRA fine-tuning.
- Built RAG systems and prompt-engineering pipelines used in research projects.
- Hands-on experience with vector databases and modern model fine-tuning workflows.
Focus
Practical AI systems — RAG, fine-tuning, and agentic LLM architectures applied to real-world data problems.