Hi! 👋
My name is Enes.
I’m a software engineer specializing in building (and occasionally designing) exceptional digital experiences. Currently, I’m focused on building accessible, human-centered products.
I code with |
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_background
Muğla Sıtkı Koçman University
Preparation School
Grade: 88.8/100
2019-2020
Muğla Sıtkı Koçman University
Computer Engineering
GPA: 3.40/4.00
2020-2024
Avalanche
Content Creator
I created social content to spread awareness about blockchain technology and the Avalanche Network.
2021-2023
Freelance Full Stack Engineer
Self-Employed
Focus: Developed robust web applications, optimized backend systems, and implemented modern tech stacks.
2023-Present
Idamobile
Fullstack Engineer Intern
Architected integrations, resolved legacy project issues, and developed reusable components.
May 2024 - July 2024
_skills
Front-End Stack
HTML,CSS,Javascript,React.js,Next.js,Vite,Redux,Context API,Bootstrap,Tailwind CSS,Material UI,Ant Design, Web3.js,Ether.js,SCSS.
Back-End Stack
Node.js,Express.js,MongoDB,Firebase,MySQL,PostgreSQL
Programming Languages
Javascript,Typescript,Java,Python,SQL,R.
Tools & Programs
Git,Visual Studio Code,R Studio,Postman,Eclipse,Pycharm,IntelliJ IDEA,Figma.
_projects
Dental Clinic Website
This project features a robust dental clinic website built with a clean architecture using Next.js and TypeScript. The site is designed with HTML and CSS, offering a modern, responsive layout and seamless user experience. The architecture focuses on performance and maintainability, ensuring the site is both scalable and easy to manage. The website effectively presents the clinic's services with clear navigation and a user-friendly interface.
Lorem Software
This project features a professional software company website named Lorem Software. Built using Next.js, TypeScript, HTML, CSS, and Redux, the site combines a sleek design with a robust architecture. The website showcases the company's products and services with an intuitive, responsive layout, ensuring a seamless user experience. With its clean design and powerful functionality, the website effectively represents Lorem Software's online presence and supports the company's business goals.
Cubic Sphere
Cubic Sphere is an open-source event-driven social media web application designed to facilitate social interactions by offering event and location-based matching. This platform enables users to connect with others through shared interests and events, fostering meaningful social connections. The tech stack used in this project includes React.js, Vite.js, HTML, CSS, and JavaScript for the frontend, and Express.js with MongoDB for the backend, ensuring a robust and scalable architecture.
BlokSeçim
This project aims to create an online platform that integrates decentralized blockchain technology to centralize information on government and company decisions. It features a blockchain-based voting system to enhance transparency and public participation. The goal is to democratize decision-making by offering a reliable and user-friendly platform for increased community engagement.
Olympic Sailing Simulator
The game simulates Olympic-style sailing competitions where players navigate a predetermined route, collecting buoys in a specific order to score points based on sailing time. Realistic wave and wind mechanics, along with dynamic water surface interactions and a visual shader, enhance gameplay realism. Players must follow Olympic sailing rules, including adhering to the course and crossing the finish line, with the goal of achieving the shortest time for top rankings.
Podia Clone
The Podia Clone project has advanced my skills in HTML, CSS, and React.js to a higher level. Through building a user interface with React.js, I've gained practical experience in creating dynamic and responsive web applications. This project has deepened my understanding of frontend development and enhanced my ability to design engaging interfaces. Overall, it has been a valuable learning experience that has strengthened my frontend skills significantly.
Stroke Detection Project
The Stroke Detection project utilizes various machine learning algorithms to predict whether individuals have experienced a stroke based on parameters such as age, gender, and occupation. By leveraging the capabilities of the ggplot library, the project provides visualizations to enhance data analysis and interpretation. Through the integration of machine learning models and visualization techniques, the project aims to improve stroke detection accuracy and facilitate informed decision-making in healthcare settings.
_contact
Thanks for visiting my website, visitor.
If you have any questions, suggestions, or just want to say hello, feel free to reach out. I am always open to new connections and collaborations!
For other projects, you can take a look at my GitHub account. ✔️
Feel free to connect with me on socials!