🎓 Final-Year B.Tech student in Electronics and Telecommunication Engineering at MIT Academy of Engineering, Pune.

🤖 Passionate about Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI.

💻 Experienced in building AI-powered applications using Python, FastAPI, Retrieval-Augmented Generation (RAG), NLP, Computer Vision, and Machine Learning.

🚀 Interested in developing scalable AI systems, intelligent automation, and real-world AI applications.

🎯 Actively seeking AI/ML Engineer, Generative AI Engineer, and Python Developer opportunities.

SmartBridge (SkillWallet) | Jun 2025 – Aug 2025

• Completed an experiential AI/ML internship focused on Python, Machine Learning, and real-world project development.
• Built practical skills in data preprocessing, feature engineering, model development, and model evaluation.

YBI Foundation | Jun 2024 – Jul 2024

• Completed a project-based internship focused on Python programming and application development.
• Strengthened programming fundamentals, OOP, file handling, exception handling, debugging, and problem-solving skills.

TLogic Foundation | Jan 2024 – Feb 2024

• Developed responsive web applications using HTML, CSS, JavaScript, and backend form processing with database integration.
• Gained hands-on experience in full-stack web development and responsive UI design.

🔗 https://github.com/kompalwargangotri/gramnet-ai-offline-multilingual-rag-tutor

Offline multilingual AI tutor powered by RAG, TinyLLaMA, FastAPI, FAISS, and SentenceTransformers for intelligent learning in low-connectivity environments.

Tech Stack: Python • FastAPI • TinyLLaMA • FAISS • SentenceTransformers • RAG • Flutter

🔗 https://github.com/kompalwargangotri/video-kyc-aml-detection

AI-powered Video KYC and AML fraud detection system integrating YOLOv8, DeepFace, Tesseract OCR, liveness detection, and Isolation Forest for secure identity verification.

Tech Stack: Python • FastAPI • YOLOv8 • DeepFace • OpenCV • Tesseract OCR • SQLite

🔗 https://github.com/kompalwargangotri/nephropredict-ai-ckd-detection

Machine Learning-based healthcare application using Random Forest for early Chronic Kidney Disease prediction with 90.96% accuracy.

Tech Stack: Python • Scikit-learn • Random Forest • Streamlit • Flask

🔗 https://github.com/kompalwargangotri/ai-energy-consumption-prediction

Machine Learning-based energy forecasting and optimization system using Support Vector Regression (SVR) with Streamlit deployment.

Tech Stack: Python • Scikit-learn • SVR • Streamlit • Pandas

• Large Language Models (LLMs)
• Agentic AI
• LangChain & LangGraph
• Model Context Protocol (MCP)
• FastAPI & Docker
• MLOps & AI Deployment

• 🏅 Fundamentals of Deep Learning — NVIDIA
• 🏅 Advanced Course on Green Skills and Artificial Intelligence — Edunet Foundation
• 🏅 Claude 101 — Anthropic
• 🏅 AI Fluency: Framework & Foundations — Anthropic

⭐ Thanks for visiting my profile! Feel free to explore my repositories and connect with me for AI/ML, Generative AI, and open-source collaborations.