Chia-Chin Wang

National Taipei University, Ming Chuan University

Papers

Total Citations

H-Index

About

Chia-Chin Wang is a robotics researcher specializing in intelligent interactive systems and underwater autonomous vehicles. Her work bridges deep learning and robotic perception, with a focus on enabling machines to understand and interact with complex environments. In her most cited work (2020, 15 citations), Wang pioneered the application of transfer learning for object detection in underwater settings, adapting the YOLO deep learning framework to identify fish species from video streams captured by remotely operated vehicles (ROVs). This contribution addresses the critical challenge of limited labeled data in marine robotics, demonstrating how pre-trained models can be effectively fine-tuned for subsea exploration. Earlier, Wang designed an intelligent interactive service robot (2017, 3 citations) that used Kinect depth imaging for environmental perception, integrating companion and entertainment functions. Her research combines practical engineering—such as real-time video processing on ROVs—with theoretical advances in transfer learning, making her work valuable for both marine biologists and roboticists. Wang’s contributions are particularly notable for their potential applications in environmental monitoring, aquaculture, and human-robot interaction, establishing her as an emerging voice in applied robotics.