I’m Ruman Shaikh — an AI Engineer and researcher working at the intersection of machine learning, neuroscience, and healthcare. At IBM, I develop client-focused AI systems including Retrieval-Augmented Generation (RAG), fine-tuned LLMs, and robust MLOps pipelines. These projects have delivered measurable improvements in accuracy, response quality, and deployment time.
Previously at Oracle Cerner, I engineered healthcare data pipelines and optimized performance across large-scale patient datasets. My work cut query latency from days to hours, improving real-time clinical decision-making.
My research experience at NeuroMatch Academy includes work on neural network scaling laws, biologically inspired learning, and NLP model robustness. I've trained autonomous agents, analyzed neural signals, and benchmarked architectures across tasks to evaluate generalization and performance. I approach technology as a system builder and problem solver, focused on impactful solutions grounded in real-world constraints. My goal is to use AI not just to innovate, but to improve lives at scale.