Yen-Jen Chen

Associate Professor & Director of  AI Center

Over the past five years, Professor Yen-Jen Chen has demonstrated profound insights in the research of AI Power Cloud, AIoT, and Large Language Model (LLM) technologies. He has accumulated rich practical experience in the industry, publishing 16 papers in international journals and conferences, successfully securing 10 invention patents, and leading 37 industry-academia collaboration research projects as the principal investigator or co-principal investigator. The total funding for these projects amounts to NT$28,893,000.

Since 2023, Professor Chen has been collaborating with Formosa Plastics Network (FPN) on a project titled "Construction of Computing Environment Deployment and Retrieval-Augmented Generation Model." In this project, he leads the development of a Retrieval-Augmented Generation (RAG) architecture based on the open-source Taiwan LLM. By leveraging Parameter-Efficient Fine-Tuning (PEFT) and Low-Rank Adaptation (LoRA) techniques, the project has enhanced the model's understanding of domain-specific knowledge, boosting the retrieval hit rate to over 95%. Professor Chen's research achievements in this area not only introduce generative AI to Formosa Plastics Group, providing a key solution that balances security and privacy, but also effectively improves the efficiency of reviewing corporate regulations and enhances model comprehension. This work lays a solid foundation for the future development of RAG technology.

History & Purpose

Ming Chi University of Technology established the AI center in August 2019, providing more than 339.9 square meters of space to set up central offices and classrooms, and investing more than 39 million dollars in computing equipment. The center is mainly dedicated to the research and development of Industrial Artificial Intelligence. The focus of research and development is to combine industry expertise (X) and artificial intelligence (AI) technology to solve industrial practical problems in the form of industry-university cooperation (Co-Op), and cultivate AI+X talents for the industry. Details are described below:

Industrial AI Technology

• Component Failure Prediction and Establishment of Preventive Maintenance Mechanism
• Material combination, scheduling, and manufacturing process optimization
• Design and integration of private cloud, sensors and IoT
• System architecture for industrial image recognition and quality inspection
• Exploration of business intelligence and management strengthening mechanism
• Industrial Safety Inspection and Accident Prevention

Talent Education

• School: Offer AI general courses and professional credit or degree courses
• Industry: Knowledge-oriented and project-oriented education/training courses