Zhibo Zhang presenting his undergraduate research at UURAF.
Project Focus: Flexible inductive sensor array + BiLSTM-based shape reconstruction for intelligent shape monitoring.
My Research Experience
Joining the Nondestructive Evaluation Laboratory has been one of the most meaningful parts of my undergraduate experience at Michigan State University. It helped me move beyond classroom learning and see how engineering, sensing, and artificial intelligence can be combined in real research.
About the Project
My main project focuses on accurate shape monitoring using a flexible inductive sensor array and a BiLSTM-based reconstruction model. The sensor collects multi-channel signals when a flexible structure bends, and the model uses those signals to estimate curvature and reconstruct the shape.
What I Learned
This project taught me that research is not only about running a model. It also requires understanding the sensing principle, preparing data carefully, comparing methods, and explaining results clearly.
Presenting the Work
Presenting this work at the University Undergraduate Research and Arts Forum helped me organize the project into a clear story and practice explaining technical ideas to people from different backgrounds.
Looking Forward
This experience strengthened my interest in intelligent sensing, machine learning, and engineering research. In the future, I hope to continue working on systems that combine physical sensors with AI for real-time monitoring, robotics, and edge AI applications.
The BiLSTM model processes a 16-channel sensor sequence and predicts curvature information for shape reconstruction.
Acknowledgement
I am grateful to Professor Yiming Deng, Lei Peng, and the Nondestructive Evaluation Laboratory for their guidance and support throughout this undergraduate research experience.