AI Systems Engineer • Prompt Infrastructure Researcher • Incoming Director of Technology @ UGAHacks XII
BS Computer Science / MS Artificial Intelligence — University of Georgia (May 2027)

Founder & Technical Lead

A scalable prompt-sharing ecosystem treating prompts as version-controlled engineering artifacts.

• Architected FastAPI backend deployed on AWS
• Designed JWT-secured authentication + PostgreSQL relational schema
• Implemented fork-based prompt lineage tracking
• Structured alpha experiment comparing isolated vs collaborative prompting workflows
• Designed roadmap for embedding-based semantic search
• Developing multimodal prompt representation + execution tracking infrastructure

Focus: prompt lifecycle management, reproducibility, cross-model benchmarking, collaborative prompt systems

Real-time American Sign Language recognition system.

• Built computer vision inference pipeline
• Applied deep learning classification models
• Designed accessibility-focused communication tooling
• Awarded hackathon victory for technical innovation

Retro-style embedded musical instrument.

• Integrated analog inputs + Mozzi-based C++ audio encoding
• Designed full embedded architecture from scratch
• Won First Prize for innovation and technical execution

Privacy-first emotional support system.

• Integrated Anthropic Claude Sonnet API
• Iterated through 50+ prompt refinements
• Designed NLP-based crisis detection logic
• Built full React frontend + secure backend interaction layer

Founded LLM Labs to explore scalable infrastructure for:

• Prompt engineering as maintainable “promptware”
• Retrieval-Augmented Generation (RAG)
• Embedding-based semantic retrieval
• LLM evaluation + reproducibility frameworks
• Agentic multi-step orchestration systems

Research direction bridges:

Prompt engineering × Backend systems × Reliability × Scalable AI infrastructure

• FastAPI microservices
• RESTful API contracts (OpenAPI/Swagger)
• PostgreSQL relational schema design
• AWS deployment pipelines
• JWT-based authentication flows
• Supabase integration
• Logging + telemetry for prompt evaluation

• Fork-based version control for prompts
• Structured reasoning templates
• Execution metadata tracking
• Cross-model benchmarking workflows
• Embedding-based semantic search roadmap

• Prompt robustness analysis
• Evaluation-driven iteration
• Secure-by-design LLM application architecture
• Studying failure modes in prompt-driven systems

University of Georgia
BS Computer Science / MS Artificial Intelligence
Expected Graduation: May 2027

Relevant Coursework:
Systems Programming • Software Engineering • Data Structures • Computer Architecture • Biomedical Image Analysis • Data Science • Theory of Computing • Discrete Mathematics • Computational Science

• 🥇 UGAHacks X First Prize — Hardware Category
• 🥇 Clemson Hacks Winner — ASL Quick Draw
• MTA Software Development Fundamentals (Certified 08/2023)
• AI For Everyone (Certified 06/2024)
• Introduction to Generative AI (Certified 06/2024)
• Introduction to RAG (Certified 08/2024)

• Incoming Director of Technology — UGAHacks XII

  • Overseeing full technical infrastructure for UGA’s flagship hackathon
  • Leading architecture, deployment strategy, and engineering operations

• Founder — LLM Labs

• Backend Committee Lead + KRONOS Server Chair — Kappa Theta Phi

• President — UGA Hindu YUVA

• Technical Lead — 501c3 Non-Profit

• Scaling prompt lifecycle tooling
• Embedding-based retrieval infrastructure
• LLM evaluation methodology
• AI system reliability + robustness
• Infrastructure design for production LLM applications

Build scalable AI systems that:

• Improve reliability and reproducibility
• Reduce duplicated prompt effort
• Enable collaborative prompt engineering
• Bridge research methodology with production deployment

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