Ankara, Türkiye
As a Systems Engineer at HAVELSAN, I specialize in tactic environmental simulation systems. My work includes developing and implementing object detection and tracking systems for unmanned systems, advancing autonomous navigation capabilities. I also contribute to swarm unmanned aerial vehicle projects by ensuring effective subsystem integration for vision-based initiatives. I have an upper-intermediate (B2) level of English. I completed a six-month intensive English course in Manchester, United Kingdom. The course was fully self-funded. I hold a Bachelor's degree in Computer Engineering from Erciyes University, where I built a strong foundation in software development, project management, and Python programming. Passionate about innovation, my focus is on enhancing autonomous systems and driving advancements in unmanned aerial and ground vehicle technologies. I am proficient in many programming languages, thanks to the projects I have carried out during my academic years and professional career. During my studies, I actively worked as an Information Technology (IT) specialist. I enjoy keeping up with the latest technological developments. Throughout my professional career, I have written and filed multiple international patents as part of the projects I have been involved in.
• Tactic environmental simulation systems engineering • Developed and implemented object detection and tracking systems for unmanned systems, enhancing autonomous navigation capabilities. • Conducted comprehensive dataset research, labeling, and augmentation to optimize model performance. • Collaborated on the assembly of swarm unmanned aerial vehicles, ensuring effective subsystem integration for vision-based projects.
I have researched and analyzed object detection algorithms. Than I have developed object detection application for unmanned ground vehicle.
I've develop data transfer application with Python and RabbitMQ.
I developed an image labeling application for breast and colon cancer datasets using Python and OpenCV. The application was used by doctors. I also applied basic Machine Learning algorithms for diabetes classification, including K-Nearest Neighbors (KNN), Random Forest, and Support Vector Machine (SVM).
I've searched open source map applications and sdks. These are Leaflet and Cesium. I've done presentation about these. I've coded some demo programs with JavaScript.