About Me
Recent Computer Engineering graduate with practical experience gained through internships in machine learning and software development. Worked with Python, TensorFlow, React, Next.js, and Java Spring Boot during internship and personal projects. Developed foundational skills in machine learning, frontend, and backend development.
Experience
Software Development Intern
Storade
September 2024 – April 2025
- Applied clean code and SOLID principles in modular web application architecture
- Developed reusable UI components using component composition and atomic design
- Created a comprehensive design system with semantic tokens and typography rules
- Implemented version control best practices including feature branching and code reviews
- Collaborated in an agile environment with sprint planning and iterative delivery
Artificial Intelligence Intern
İ.Ü. Teknoloji Transfer Uygulama ve Araştırma Merkezi - TETLAB
July 2024 – August 2024
- Developed CNN model for skin disease image classification
- Applied various optimization techniques to improve model performance
- Gained practical experience with Python and TensorFlow ecosystem
- Acquired project documentation and GitHub management skills
Featured Projects
PlantAssist: AI-Powered Plant Care Assistant
Flutter, Dart, Firebase, SQLite, PlantNet API, Plant.id API, Gemini API
- Developed cross-platform mobile app achieving 86% plant identification accuracy
- Integrated multiple AI systems for identification and personalized care recommendations
- Implemented cloud and local data synchronization with Firebase and SQLite
- Applied modular design patterns and effective state management for scalability
HRMS (Human Resource Management System)
Spring Boot, Spring Data JPA, Hibernate, PostgreSQL, Swagger
- Built comprehensive backend system with layered architecture for HR management
- Developed RESTful APIs for user management, job posting, and application workflows
- Designed relational database models using JPA/Hibernate for robust data management
- Integrated Swagger for API documentation, facilitating easier front-end integration
Mental Health Data Analysis
Python, Pandas, NumPy, Scikit-learn, TensorFlow, Matplotlib
- Analyzed 290,000+ records to predict mental health treatment needs
- Compared ML algorithms and deep learning models to achieve 73.6% F1-score
- Performed feature selection to identify key predictors of treatment-seeking behavior
- Optimized model selection balancing computational efficiency and performance
Skills
Programming Languages
Java, Python, JavaScript, Dart
Frameworks & Libraries
Spring Boot, React, Next.js, Flutter, TensorFlow, Keras
Databases
MySQL, PostgreSQL, Firebase, SQLite, JPA/Hibernate
Tools & Practices
Git, GitHub, Docker, CI/CD, Agile, REST API, SOLID Principles, Clean Code
Education
Computer Engineering
Biruni University
October 2021 – June 2025
GPA: 3.12/4.00