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Undergraduate Researcher
Georgia Tech Research Institute (GTRI)
LLM Inference Optimization Team
Atlanta, GA
Jan 2025 -- Present
Technologies
PythonPyTorchSLURMDeepseek-R1Convolutional Neural Networks
Key Achievements
- Developing Retrieval-Augmented Generation (RAG) system for LLM guided evolutionary neural architecture search with domain-specific corpus, improving context for CNN mutations with target 15-25% performance baseline improvement
- Engineered distributed fitness inheritance system with checkpoint aware seeding, eliminating 16+ redundant GPU evaluations per run and reducing generation time by 35% across 12 generation cycles on CIFAR-10 data
- Implemented server-side request batching with retry logic and load balancing with least connections algorithm, reliably achieving sub-250s average end-to-end latency across 52 evaluations per SLURM run with Deepseek-R1
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