I build software at the intersection of systems performance and machine learning — writing tools that are fast by design, not by accident. My focus is on the lower layers of the AI stack: model optimization, efficient inference, and the infrastructure that bridges research with production.
Currently pursuing a degree in Computer Science, and specialized in Data Science, while discovering the depth of LLM and learning its infrastructure.
I like Deep Neural Network.
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ML Infrastructure Neural network quantization, model compression, ONNX pipelines, and inference optimization. Basically, discovering different aspects of LLM related. |
Applied AI NLP, sentiment analysis, LLM integration, and AI-assisted applications. Translating model capabilities into usable products. |
Systems & Web Full-stack applications in TypeScript and React Native, static tooling, and developer utilities — built with the same rigor as the ML work. |
Open to collaboration on ML infrastructure, developer tooling, and applied AI projects.
