First place at the National Taiwan Normal University Mechatronic Capstone Competition (2023), the department’s flagship hands-on contest, where teams are judged on a complete working mechatronic system rather than a slide deck.

The winning entry was my Smart-Manufacturing Quality Prediction System: an AI model that predicts a product’s weight to within 0.2% straight from live sensor signals, backed by real-time signal processing, a PyQt5 operator dashboard, and an SQL traceability layer. What the judges rewarded was the end-to-end integration: sensing hardware, the signal chain, machine learning, and software brought together into one reliable system that held up under competition conditions.

The same work went on to be published at the 2023 ARIS International Conference and recognized again with a Bronze Prize at the Symtek Smart Manufacturing Paper Contest.