Arian Rezazadeh Monfaredniya
Always learning. Always building...
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About Me
Hello, World!
I am Arian Rezazadeh Monfaredniya, a Software Engineering graduate with a deep passion for developing efficient, reliable, and user-centric applications.
I began my academic journey with an Associate’s Degree in Software Engineering from Mollasadra Technical and Vocational College in Ramsar (2019–2021), and subsequently earned my Bachelor’s Degree at Chamran Technical and Vocational College in Rasht (2023–2025). Throughout this journey, I cultivated a strong foundation in programming, algorithms, and contemporary software development methodologies.
My primary areas of interest encompass Software Engineering, Artificial Intelligence (AI), Machine Learning, Cybersecurity, and Penetration Testing. Beyond formal education, I have continually enhanced my skills through personal projects and by actively engaging with emerging technologies and industry advancements.
Currently, I am preparing to pursue a Master’s Degree to deepen my expertise and specialize further in these domains. My long-term ambition is to collaborate with innovative teams and forward-thinking organizations, contributing to research and projects that generate meaningful and lasting impact.
Let’s connect and create something extraordinary together!
GitHub Contributions
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Experience
Freelance
Education
Projects(7)
An advanced web-based framework for classifying various skin cancer types using deep learning and TensorFlow.js. Users can upload dermoscopic images of skin lesions to receive predictive insights into potential skin cancer diagnoses.
Algorithms Used:
- 🧠 Deep Learning: Convolutional Neural Networks for image classification.
- ⚡ TensorFlow.js: Client-side machine learning for real-time inference.
- 📊 MobileNet Model: Pre-trained model optimized for web deployment.
Features:
- 🕒 Real-Time Detection: Instantaneous predictions with TensorFlow.js.
- 📋 Multi-Type Classification: Identifies multiple skin cancer types.
- 🖱️ Drag-and-Drop Interface: Easy image upload functionality.
- 🖼️ Demo Images: Evaluate the model's capabilities with sample images.
- 📊 Detailed Predictions: Top 3 classification results with confidence scores.
- 📱 Responsive Design: Optimized for mobile and desktop.
- 📈 Interactive Visualization: View predictions through dynamic charts.
- Python
- TensorFlow.js
- Keras
- OpenCV
- HTML5/CSS3
- JavaScript
- Chart.js
- MobileNet
- Jupyter Notebook
