Barış GÜNGÖR

This project is a web-based, real-time messaging and voice calling application developed using HTML, CSS, JavaScript, Node.js, Express.js, Socket.io and MySQL, designed to explore web application capabilities and establish a small-scale communication ecosystem within a classroom or department. My contributions including database design, application connectivity, seamless frontend-backend integration, the development of core messaging features, and the implementation of search functionalities, make this project my most extensive and rewarding development experience, significantly enhancing my individual problem-solving skills and fostering exceptional team time management. For my graduation project, I plan to expand the application by integrating video calling functionality and deploying it for public access.

Our project aims to predict the memorability of video content using machine learning methods. Within the scope of this project, a model will be developed that can classify videos into low or high memorability levels based on visual features. This research project will contribute to fields such as marketing, digital advertising, and education. So far, we have created memorability classes for videos in the publicly available VideoMem and Memento10K datasets and trained the model based on specific visual features (e.g., HOG). We presented our work at UBMK 2025 and are now preparing a paper for the "Memorability" task organized within the scope of the MediaEval 2025 workshop.

This project involved developing a desktop-based library management system for our department's newly established library, designed for immediate implementation to streamline book management, user registration, and overall library operations. Utilizing Python, PyQt5, MySQL, and Qt Designer, the system provides an efficient and user-friendly interface. As part of a three-member team, my contributions centered on backend development, database design and data management, ensuring the system's reliability and functionality. This project significantly strengthened my research skills and deepened my understanding of real-world software development. As my first collaborative team project, it effectively bridged the gap between theoretical knowledge and practical application, while also enhancing my communication and teamwork abilities.

ScheduleX is an application designed to generate optimal class schedules by factoring in course availability, classroom resources, instructor schedules, and user-defined priorities. Users can assign priority levels to courses based on their importance, while classrooms are selected according to their capacity, equipment, and specialized requirements. Instructor availability is also integrated into the schedule generation process. This ensures that high-priority courses are scheduled effectively, and classrooms and instructors are assigned based on their specific needs and preferences. The application aims to streamline school management processes, ensure consistent class delivery, and optimize time and resource utilization. The documentation was completed by a team of six, and the coding phase is finished with a team of five, following the departure of three members and the addition of two new members.

AttendX is a digital attendance management system designed to streamline university attendance processes. Developed by a team of six, I contributed to documentation and communication. The system comprises a web interface (AttendX-Hub), a mobile application (AttendX-Terminal), and a Java-based backend. Key features include automated attendance tracking, real-time performance monitoring, and comprehensive reporting for students and teachers. Built with React, Spring Boot and Docker, AttendX ensures cross-platform compatibility, data security, and scalability. Future enhancements include AI integration to improve user experience and efficiency.