I am a Computer Science student specializing in computer vision, machine learning, and edge computing. At FLARE Darmstadt, I am developing wildfire detection systems using UAVs and AI, focusing on efficient computer vision algorithms and YOLO-based object detection. I also have experience in game development, full-stack web development, and Python projects, emphasizing lightweight systems for challenging environments. My goal is to advance AI technologies that solve real-world problems, with a focus on real-time, reliable applications in computer vision and edge computing. I am expanding my skills in deep learning frameworks. Long term, I aim to lead research efforts that connect academic innovation with practical solutions in environmental monitoring, autonomous systems, and intelligent automation.
Native or bilingual proficiency
Full professional proficiency
Native or bilingual proficiency
Native or bilingual proficiency
Growing up in a multicultural environment and studying in Germany has given me a unique perspective on cross-cultural collaboration and communication. This diversity in my background helps me work effectively in international teams and understand different approaches to problem-solving.
Constantly seeking new ways to solve complex problems with creative AI solutions.
Building technology that makes a positive difference in environmental protection and safety.
Working with diverse teams to create solutions that combine different perspectives and expertise.
I'm always excited to connect with fellow developers, researchers, and anyone passionate about AI and technology.