Aspiring AI Engineer & Data Scientist — continuously building, learning, and shipping production-ready solutions at the intersection of intelligence and engineering.
I'm an aspiring Data Analyst and AI Engineer pursuing B.Tech in Computer Science & Engineering at Brainware University, West Bengal. Continuously sharpening my craft at the intersection of Data Science, Quantitative Engineering, and Generative AI.
My mission: transform complex, real-world problems into fast, production-ready AI solutions using cutting-edge LLMs, agentic workflows, and cloud infrastructure. Every project I build is live, verifiable, and production-deployed.
Completed an intensive, industry-structured AI training program covering Machine Learning fundamentals, Deep Learning architectures, and real-world AI model development. Independently engineered a Product Demand Forecasting System using advanced time-series analysis and predictive modeling — directly supporting data-driven supply chain decision-making in a production-grade environment.
Completed comprehensive end-to-end courses covering Python programming, Machine Learning, Deep Learning, Generative AI, and MLOps — with an emphasis on real-world project development and production-ready deployment practices across cloud and local environments.
Pursuing B.Tech in CSE with focus areas in AI, Machine Learning, Data Science, and Quantitative Engineering. Actively building and shipping real-world AI projects alongside academic coursework — bridging theory with production-grade implementation.
End-to-end financial forecasting pipeline leveraging deep learning models and quantitative analysis. Ingests and preprocesses historical market data, applies advanced LSTM-based time-series modeling, and generates actionable predictive signals for financial decision-making. Includes rigorous backtesting frameworks and model evaluation metrics for production-grade reliability and generalizability in real financial environments.
VIEW PROJECT →Fully autonomous AI agent system executing complex, multi-step tasks with minimal human intervention. Features custom agentic workflows, tool-use integration, dynamic memory management, and context persistence across sessions. Deployed to AWS EC2 with automated CI/CD via GitHub Actions.
VIEW PROJECT →All live deployments, source code, and detailed documentation available at my portfolio site. Continuously updated with new AI experiments, projects, and research explorations.
VISIT PORTFOLIO →Open to collaborations, internships, and opportunities in AI engineering, data science, and quantitative development. Let's build something extraordinary together.