I am a pre-final year Computer Science student at Siksha 'O' Anusandhan University. My technical focus lies in designing intelligent systems, deploying computer vision architectures, and building production-ready scalable backends.

• 🔭 Currently Building: Ai attendance tracker, an advanced AI assistant utilizing Retrieval-Augmented Generation (RAG) and Llama 3.
• ⚙️ Engineering Focus: Computer Vision, Natural Language Processing, Deep Learning, and Multi-Agent LLM architectures.
• 🏆 Competitive Programming: Solved 500+ problems across LeetCode, CodeChef, and Codeforces (LeetCode Rating: 1416).
• 🤝 Open to Collaboration: Deep learning research, FinTech automation, and open-source AI tooling.

Programming Languages

AI, Machine Learning & Computer Vision

Backend & Architecture

• Role: Lead AI Developer
• Accolades: Semi-finalist at the Tata Innovent Hackathon
• Tech: Python, Computer Vision, Mediapipe
• Description: Engineered a real-time driver safety monitoring system. Implemented Eye Aspect Ratio (EAR) and Mouth Aspect Ratio (MAR) algorithms to accurately detect drowsiness and prevent potential accidents.

• Tech: LangGraph, ChromaDB, Python
• Description: Designed a sophisticated AI customer support architecture. Orchestrated a multi-agent system utilizing specialized agents (Triage, Retriever, and Compliance) to handle complex, domain-specific e-commerce queries accurately and securely.

• Engineering high-performance backend systems
• Designing scalable APIs and distributed architectures
• Solving complex algorithmic problems
• Building real-world, production-ready applications

• System Design (Scalability, Caching, Load Handling)
• Backend Development (Node.js, APIs)
• Data Structures & Algorithms
• Database Optimization

• Build systems, not just projects
• Optimize for scalability from day one
• Prioritize clarity and maintainability

Focused on transitioning from learning to building production-grade systems with measurable impact.