"Building intelligent systems that bridge the gap between cutting-edge AI research and real-world applications"

🎓 Computer Science Undergraduate | University Institute of Technology, Burdwan
🤖 AI/ML Enthusiast specializing in Large Language Models and Generative AI
⚡ Current Focus: RAG Pipelines, LLM Deployment, and Multimodal AI Systems
🌱 Always Learning: Latest developments in AI/ML and emerging technologies
🎯 Goal: Contributing to the future of AI through innovative research and applications

• CGPA: 8.81/10 (Current)
• Specialization: Machine Learning, Deep Learning, Generative AI
• Research Interests: LLMs, RAG Systems, Low-Resource Language AI

Advanced ML-powered healthcare solution

• 🎯 Impact: Diagnoses 5+ diseases with 80-90% accuracy
• 🛠️ Tech: Python, Streamlit, Scikit-learn, Medical Datasets
• ✨ Features: Intuitive UI for non-technical users, Real-time predictions
• 📊 Models: Diabetes, Cancer, Heart Disease, Parkinson's, Hypo-thyroid detection

LangChain-powered intelligent document processing

• 🤖 AI Model: Gemini 2.0 Flash API integration
• 🎤 Features: Interactive Q&A, Voice-to-text summarization
• 🔐 Security: Secure API management with Streamlit Secrets
• 🚀 Deployment: Production-ready with robust error handling

High-performance digit recognition system

• 🎯 Accuracy: 98%+ on handwritten digit classification
• 🧠 Architecture: Optimized CNN with advanced preprocessing
• 🎨 Interface: Interactive drawing pad for real-time testing
• ⚡ Performance: Optimized for fast inference

Computer vision-powered emotion recognition

• 📹 Real-time: Live facial emotion detection via webcam
• 🎭 Emotions: Happy, Sad, Angry, Surprise, Fear, Disgust, Neutral
• 🔬 Dataset: FER-2013 with custom data augmentation
• 🖥️ Integration: OpenCV + Streamlit deployment

AI Intern | TechSaksham (Microsoft & SAP CSR Initiative) | Feb-Mar 2025

• Collaborated on real-world AI projects under expert mentorship
• Gained exposure to responsible AI practices and data ethics
• Participated in advanced workshops on Microsoft AI tools