About

I am from Taiwan and currently pursuing a Master’s degree in Electrical Engineering at HTWG Konstanz in Germany. My primary interest lies in software development for electrical applications, complemented by a focus on machine learning and embedded systems.

During a software development internship at Hoval in Liechtenstein, I worked on a Modbus configurator for heat pump systems. I optimized scripts with JavaScript through modularization, reducing system configuration and testing time. I also wrote unit tests using Jest, enhancing the tool’s reliability.

For my Bachelor’s thesis, I implemented and compared three different models in Python for electricity consumption forecasting: a deep learning approach (LSTM), a machine learning method (XGBoost), and a statistical technique (ARIMA). The goal was to determine which model provides the best prediction accuracy with the shortest training time.

As part of a collaborative project during my studies, my fellow students and I developed an embedded system for real-time wind condition monitoring to optimize wind power applications. We utilized Arduino as the main controller, integrating Modbus for sensor communication and MQTT for data transmission.

When not working, I can be found on the basketball court or in the kitchen, cooking spicy Asian specialties.