Professional Computer Scientist and Researcher in Artificial Intelligence I hold a B.Sc. in Computer Science from AASTMT (2018), and I’m currently finalizing my M.Sc. degree in Computer Science, expected in February 2025. My graduate thesis focuses on Peer-to-Peer Federated Learning, where I develop decentralized learning algorithms to enhance the scalability and performance of distributed AI systems. My research centers on intelligent, networked, and distributed systems—especially in the area of privacy-preserving machine learning such as Federated Learning. Through a collaborative project between AASTMT and the University of Vigo (Atlantic Lab, Spain), I’ve contributed to advancing communication and scheduling schemes in decentralized FL, earning the Best Paper Award at ICCTA 2022. As a Teaching Assistant at AASTMT since 2019, I have taught over nine computer science courses covering programming, data structures, embedded systems, and robotics. I also serve as a competitive programming coach and academic advisor. Beyond the university, I teach robotics and coding to kids, fostering STEM education through community initiatives like Robotak. In industry and freelance roles, I’ve worked on diverse projects in web development, IoT, and system automation. One of my key projects, WE-CARE, is an IoT-enabled school bus tracking system built with Raspberry Pi, GPS, and mobile integration, developed with ROOT-Technologies. I aim to advance the field of computer science through both research and practical innovation. I enjoy learning languages, listening to tech podcasts, drinking coffee, and spending quality time with family.