Chung-Hsien Tsai

Associate Professor
Department of Information Management, Southern Taiwan University of Science and Technology
Intelligent Computing and Network Communication Laboratory (ICNCLAB)

Auditable scaffolding for AI agents in teaching settings, and the resilience of communication and sensing systems under degradation.

My work began in sensing and human–computer interaction and has moved toward how systems behave under conditions that are not ideal. Early on the question was how a system could infer a user's situation — improving positioning with context-aware techniques, switching augmented-reality content according to behaviour. A middle period addressed measurement problems in imagery, including UAV orthoimage registration and video foreground detection. Recent work concentrates on two things: how much function communication and sensing systems retain under degradation, and what auditability means once AI agents enter a teaching setting.

Before my academic career I served as an officer across aircraft maintenance, software engineering, operations training, and information supervision. That period shaped how I read a system: ask what remains when it breaks before asking how well it performs when it does not.

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