rahulrahul rahul

About

Computer science and data science student with experience in app development and full-stack/project work. Built multiple AI, web, mobile, and ML projects using modern frameworks and developer tools.

Experience

• Software Development Intern
  Khaga Enterprises · Banglore
  Jul 2024 – Jan 2025

  Worked as an app developer on Apartment Security Control (ASC), handling coding, testing, and collaboration with team members to deliver solutions. Integrated backend code with UI/UX designs by coordinating with frontend developers.

Education

• MTech in Computational and Data Science
  National Institute of Technology Karnataka, Surathkal
  Computational and Data Science · Aug 2025 – 2027
• Bachelor of Engineering in Computer Science
  JSS Academy of Technical Education
  Computer Science · Dec 2020 – Jun 2024

Skills

• SQL
• C
• CSS
• FastAPI
• HTML
• Python
• JavaScript
• Django
• Matplotlib
• NumPy
• Pandas
• scikit-learn
• LangChain
• OpenAI API
• Testing
• LangGraph
• Google Gemini Api
• app development

Projects

• Cook Tutor App
  Flutter

  Cross-platform mobile app for interactive culinary tutorials, recipes, personalized feedback, and progress tracking.

• Voice-based Transport Enquiry System
  Django, JavaScript

  Voice-activated transportation inquiry system with speech recognition and Django backend integration for real-time transit information.

• Pump Anomaly Detection using Machine Learning
  Python, Scikit-Learn, XGBoost, Prophet

  Built predictive maintenance models for industrial pump systems with preprocessing, feature analysis, classification, and time-series forecasting.

• LeetSensei | AI-Powered LeetCode Tutor
  JavaScript, HTML/CSS, Chrome API (Manifest V3), Gemini AI

  Chrome extension that integrates Gemini AI into LeetCode for real-time tutoring, DOM extraction, dynamic sidebar UI, and persistent chat history.

• Agentic AI Workflow Orchestration Platform
  Python, LangGraph, LangChain, FastAPI

  Built a multi-agent AI orchestration platform that routes user requests to specialized agents based on intent and coordinates workflow execution.

• Self-Healing Enterprise RAG Assistant
  Python, LangChain, Hugging Face, Vector Databases, FastAPI

  Designed a closed-loop, self-healing RAG architecture with source-grounded answers, retrieval failure detection, HyDE, two-stage retrieval, CRAG logic, and a continuous learning pipeline.