Mincheol Shin

As a researcher at Dr. Jinoh Kim’s lab, I contributed to advancing 5G network security through enhanced machine learning models. I developed a GRU-based model that achieved a 98.9% F1 score in UAV anomaly detection and implemented a Transformer-based model utilizing masked language modeling (MLM) techniques, reaching a 98.0% F1 score. These projects allowed me to build expertise in Python and PyTorch. I covered the entire pipeline, from data preprocessing to model implementation, design and deep learning model optimization.

In addition, I worked as a fashion model and creator at Samsung C&T, where I contributed to content planning and execution. This experience enhanced my creativity, adaptability, and communication skills, complementing my technical background. I perform exceptional in environments that require collaboration and problem-solving skills.

• Shin, Mincheol et al. “Trajectory-Driven Deep Learning for UAV Location Integrity Checks.” IEEE access 12 (2024): 178789–178804. Web.
• Shin, Mincheol et al. “Intelligent Trajectory-Based Approach to UAV Location Integrity Checks.” 2024 33rd International Conference on Computer Communications and Networks (ICCCN). IEEE, 2024. 1–9. Web.