✨ I’m a Data Science student at The University of Sheffield, exploring the frontier of LLMs, RAG systems, agentic AI, and multi-agent workflows.
🌙 My work blends clean engineering with the smooth, minimal aesthetic precision, and clarity.
🧩 I enjoy designing fast, scalable, and thoughtful AI systems that solve real-world problems.
⚡ I believe in constant iteration — learning, experimenting, refining, improving.
📡 Currently exploring advanced NLP pipelines, embeddings, retrieval systems, and high-performance inference.
🎯
Focusing
AI/ML engineer studying Data Science at the University of Sheffield. I build LLM-driven and multi-agent AI systems, while pursuing cinematography as my creative
- Sheffield
- in/vedant-ghadigaonkar-2bb022231
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Sheffield-caz-analysis
Sheffield-caz-analysis PublicTime series analysis of Sheffield's Clean Air Zone effectiveness: ARIMA forecasting, Prophet modeling, ITS regression. Proven 30-44% NO₂ reduction with statistical significance (p<0.001). Complete …
R
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LexLegal
LexLegal PublicState-of-the-art Adaptive RAG pipeline engineered to solve 'Lost in the Middle' retrieval failure in dense legal documents. Features semantic-sliding ensemble chunking and a sophisticated query-sco…
Python
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Lex-Router
Lex-Router PublicA domain-agnostic, zero-dependency adaptive query router for RAG systems. Optimizes retrieval strategies using multi-signal statistical analysis of pilot scores.
Python
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