Software Engineering student at İzmir University of Economics focused on backend engineering, scalable systems, API architecture, and performance-oriented software design.

Interested in building reliable backend services, improving system performance, and designing maintainable software architectures.

• Interested in backend engineering and scalable system design
• Passionate about performance optimization and maintainable architectures
• Enjoy solving engineering-focused problems and improving existing systems
• Currently learning Rust and systems programming fundamentals
• Experienced in team-based software development workflows

Linux

Bash

Python

Java

TypeScript

Rust

Node.js

Firebase

MySQL

SQLite

PostgreSQL

Flutter

Figma

Git

GitHub

Postman

Performance-oriented algorithmic trading and strategy evaluation platform focused on scalable financial data processing, quantitative analysis workflows, and efficient backtesting infrastructure.

Designed around modular data pipelines, vectorized computation, and maintainable research workflows for large-scale historical market analysis and trading strategy experimentation.

Focus Areas:

• Historical market data pipelines
• Strategy backtesting infrastructure
• Vectorized data processing with Polars & NumPy
• Quantitative trading research workflows
• Performance optimization for large datasets
• Modular and extensible system design
• Experimentation with Rust for high-performance components

Tech Stack: Python, Rust, Polars, Numpy, Financial Data Processing

Feature-modular headless CMS and website management platform designed around scalable frontend architecture, dynamic content modeling, and maintainable backend-driven workflows.

Focus Areas:

• Modular system architecture
• Dynamic content type & component builders
• REST API-driven workflows

Tech Stack: TypeScript, Node.js, PostgreSQL, REST APIs

Inspired by modern headless CMS platforms such as Strapi and Payload CMS.

Multidisciplinary Engineering Project

AI-assisted healthcare platform for chronic disease prediction and real-time health monitoring.

Focus Areas:

• AI-powered chronic disease risk prediction using XGBoost
• Personalized dietary recommendations based on clinical food data
• Real-time vital signs tracking via Flutter mobile app
• Automated SOS system for emergency health situations
• Medical lab report processing and analysis

Tech Stack: Python, Flutter, Firebase, SQLite, XGBoost

Mobile Application Development

A clean, intuitive mobile app that delivers curated news from multiple sources with enhanced content discovery.

Features:

• Cross-platform mobile application
• Category-based news navigation
• Clean, modern UI/UX design
• Real-time news updates

Tech Stack: Flutter, Dart, REST API

Artificial Intelligence and Expert Systems

An automated grading system that evaluates short-answer responses using advanced NLP techniques.

Features:

• SentenceTransformers model for semantic analysis
• Automated answer sheet processing
• Structured output generation

Tech Stack: Python, NLP, Language Processing

Thanks for visiting! Feel free to explore my projects and reach out for collaboration.