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GowthamRavuri01/README.md

Gowtham Ravuri

AI Engineer • Computer Vision Engineer • Software Engineer

Building intelligent software systems through Artificial Intelligence, Computer Vision, Machine Learning, and Python.


About

I am a Computer Science graduate with a strong interest in developing AI-powered software solutions that solve real-world problems. My experience spans Computer Vision, Machine Learning, Deep Learning, and full-stack AI application development.

During my internship, I worked on industrial Computer Vision solutions involving dataset preparation, annotation, model training, evaluation, deployment, and Python-based desktop applications. Alongside this, I have developed projects across NLP, cybersecurity, sustainability, and image classification, giving me hands-on experience in designing and deploying end-to-end AI systems.

I am currently seeking opportunities where I can contribute as an AI Engineer, Computer Vision Engineer, or Software Engineer while continuing to build scalable and impactful intelligent systems.


Technical Skills

Languages

  • Python
  • Java
  • C++
  • SQL

Artificial Intelligence

  • Machine Learning
  • Deep Learning
  • Computer Vision
  • Natural Language Processing

Frameworks & Libraries

  • TensorFlow
  • PyTorch
  • OpenCV
  • Scikit-learn
  • Ultralytics YOLO
  • Pandas
  • NumPy
  • Matplotlib

Software Development

  • Flask
  • PyQt
  • MongoDB
  • Git
  • GitHub

Featured Projects

AI-Powered Grievance Management System

An intelligent grievance management platform that automates complaint classification, routing, and email notifications using Machine Learning and Natural Language Processing.

Technologies: Python, Flask, MongoDB, Scikit-learn, SMTP


Hybrid Intrusion Detection System

Developed a hybrid Machine Learning and Deep Learning framework that combines feature selection and fuzzy logic to improve intrusion detection accuracy while reducing false positives.

Highlights

  • 98.4% Detection Accuracy
  • 18% Reduction in False Positives

Smart Rainwater Harvesting & Energy Estimation System

Developed an AI-powered desktop application that predicts water quality, harvestable rainwater quantity, and renewable energy potential using multiple Machine Learning models integrated with a PyQt interface.


Rice Grain Classification

Implemented and compared multiple Machine Learning and Deep Learning models for automated rice variety classification using image processing techniques.


Areas of Interest

  • Artificial Intelligence
  • Computer Vision
  • Machine Learning
  • Deep Learning
  • Intelligent Automation
  • Software Engineering

Connect

Pinned Loading

  1. GrievanceRedressAI GrievanceRedressAI Public

    AI-powered grievance management system using Flask, Scikit-learn, MongoDB, and SMTP automation.

    HTML

  2. Intrusion-Detection-using-ML-DL Intrusion-Detection-using-ML-DL Public

    Hybrid intrusion detection system using Machine Learning and Deep Learning models with XGBoost feature selection and fuzzy logic to improve cyberattack detection accuracy and reduce false positives.

    Jupyter Notebook

  3. Rice-Grain-Classification-Project Rice-Grain-Classification-Project Public

    Rice grain classification using Computer Vision, CNN, and Machine Learning models for automated rice variety identification through image preprocessing and comparative model evaluation.

    Jupyter Notebook

  4. Enhancing-Image-Recognition-Research Enhancing-Image-Recognition-Research Public

    Jupyter Notebook

  5. OptiPark OptiPark Public

    Jupyter Notebook