I’m Raj Chintawar, an undergrad in Computer Science & Engineering (Data Science) at GHRCEM, Pune,
aka I break things(unintentionally/intentionally) and then fix them.
I build things on the web that actually make sense. I work mainly with the MERN stack React for clean, responsive UIs, Node.js & Express for backend muscle, and MongoDB to keep data from going feral.
I can code in Java, Python, and C++ for problem Solving.
I’ve built multiple Python and web projects, learned teamwork through internships, and stay active in tech communities because shipping alone is boring.
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Title: Stock Portfolio Management base system
Stockie-Mng is a modern, full-stack stock portfolio management platform powered by AI suggestions. Built using React, Node.js, MongoDB, and OpenAI, the project helps users create, analyze, and optimise their investment portfolios with ease.
Title: ATS Focused Resume Analyzer
Built to analyze resumes the way Indian recruiters actually do — fast, strict, and unforgiving. An AI-powered system that flags resume red signals, skill mismatches, and weak project claims before a recruiter ever sees them. Designed around Indian MNC and startup hiring patterns, not generic global templates. Simulates real ATS and recruiter screening logic to deliver clear shortlist or reject verdicts. Brutally honest resume feedback with zero motivational nonsense.
A Python-based face recognition attendance system using OpenCV, DeepFace, TensorFlow, NumPy, and Pandas. It captures faces via webcam, detects and verifies them in real time, and records attendance with date and time in a CSV file. A virtual environment is used to manage dependencies and ensure smooth setup.
Title: Vehicle Detection & Motion Detection
This Python project detects and counts vehicles in a video using OpenCV. It applies background subtraction to identify moving objects, filters them by size, tracks their center points, and increments a counter when they cross a set line. The result is displayed in real-time with bounding boxes and a count overlay.
VidyaPath - Agentic AI Based Academic Planner
This project aims to build an intelligent, agentic AI system that autonomously plans, monitors, replans, and explains academic study schedules for students. The system is designed as a full-stack web application with a modular architecture separating frontend, backend, AI reasoning, and data persistence layers.
Dumb Communication and Response System
A web-based FAQ chatbot that enables users to register, log in, and interact with a predefined knowledge base. The system retrieves the most relevant response using TF-IDF vectorization and cosine similarity while securely storing user conversations and feedback.
DYNAMO – Dynamic Multi-Agent Orchestration System
DYNAMO is an AI orchestration platform that enables multiple specialized AI agents to collaborate under the supervision of an intelligent orchestrator. Instead of functioning as a traditional chatbot, DYNAMO visualizes the complete execution lifecycle—from task planning to agent execution and final synthesis—in real time.