About
AI & Data Science undergraduate with hands-on experience building LLM-powered agentic systems, production RAG pipelines, and cloud-native MLOps workflows on AWS. Skilled in Python, machine learning, NLP, and data engineering.
Projects3
Agentic Data Analysis System
Engineered a multi-agent natural language analytics platform using FastAPI and LangChain with Groq-backed inference, enabling non-technical users to query structured datasets conversationally. Built a full RAG pipeline integrating FAISS and Chroma vector stores for semantic document retrieval, achieving approximately 40% lower query latency over naive brute-force search.
- Python
- FastAPI
- LangChain
- Groq
- FAISS
- Chroma
- Pandas
NeuralOps: Cloud-Native RAG Pipeline for Autonomous LLM Intelligence
Architected and deployed a production-grade MLOps pipeline on AWS for a Retrieval-Augmented Generation system, integrating vector embeddings and containerized LLM inference APIs. Automated the full model lifecycle via CI/CD pipelines, reducing manual deployment effort and cutting estimated model update cycle time by 50%.
- AWS
- Docker
- CI/CD
- LLMs
Digital Twin Simulation System for Business Analytics
Designed a parameterized digital twin simulation engine to model complex business dynamics using historical data, enabling real-time what-if scenario analysis across pricing, demand, and customer behavior metrics. Built reusable modular ETL and simulation pipelines for efficient data ingestion and transformation.
- Python
- Scikit-learn
- Statistical Forecasting
- ETL
Education1
Bachelor of Technology in Artificial Intelligence & Data Science
2023 — 2027AISSMS Institute of Information Technology