I am a dedicated undergraduate student in the Department of Artificial Intelligence at Chang Gung University, focused on both research and practical applications of deep learning. As part of our LLM and Intelligent microservice orchestration  project in this lab, I take the lead in coordinating team tasks, offering technical insights, and managing Edge Intelligence hardware deployment. My core expertise lies in implementing deep learning models and image recognition technologies—particularly YOLO—and I continually explore new ways to leverage these skills for real-world impact. From 2024 to 2025, I am collaborating with Lin Jhe-Heng to develop a “Smart Traffic Analysis System,” which aims to help enterprises optimize vehicle flow. Alongside my AI-driven work, I have hands-on experience with containerization tools such as Docker and Kubernetes, ensuring that our solutions remain scalable and robust.

Additional  my technical pursuits, I am also an active contributor in the Chinese orchestra community, serving as a conductor, Erhu (二胡) player, composer, and arranger. Balancing both the analytical and creative aspects of my life allows me to tackle challenges with fresh ideas and a unique perspective.

I am Lin Hsuan Chen, an undergraduate student in the Department of Artificial Intelligence at Chang Gung University and a dedicated member of the Intelligent Cyber-Physical Systems Research Lab, actively contributing to the Intelligent Network Service Monitoring Analyzer project in the Intelligent Cyber-Physical Systems Research Lab. My role focuses on integrating machine learning applications with Kubernetes-based deployment, ensuring scalable and efficient service orchestration. With a strong foundation in deep learning model training, I explore ways to optimize AI-driven solutions for edge computing environments. Additionally, I have hands-on experience with cloud technologies, containerization tools like Docker and Kubernetes, and system resource management. Beyond my academic work, I am also passionate about street dancing, which complements my dynamic and problem-solving mindset.

I am Tsai Jr-Shiang, an undergraduate student in the Department of Artificial Intelligence at Chang Gung University, and a dedicated member of the Intelligent Cyber-Physical Systems Research Lab. My research interests focus on computer vision and intelligent system integration, including object detection using YOLO, person re-identification (ReID), and visual tracking. I work on integrating embedded systems, sensor data, and cloud services to develop real-time, practical intelligent applications. I emphasize system architecture design, experimental validation, and performance evaluation, with the goal of applying artificial intelligence technologies to real-world scenarios. 

Hello! I am Cheng-Ruei Yo, an undergraduate student in the Department of Artificial Intelligence at Chang Gung University. My research focuses on Natural Language Processing (NLP) and Edge Computing, with practical experience applying neural network models to real-world projects.

During my sophomore year, I contributed to an audio recognition project at a startup, where I assisted in building models and data pipelines from scratch. This experience strengthened my technical implementation skills and highlighted the importance of high-quality data collection and systematic project planning.

In my junior year, I worked with lab members on a “Smart Shopping Cart” project, leveraging Edge Computing to enhance real-time performance while reducing operational costs. Our goal is to deploy AI solutions that effectively address real-world challenges.

Beyond research, I enjoy swimming, reading, and mountaineering, activities that help me maintain focus, discipline, and balance in both academic and project work.