Driven by Industry 4.0, fermentation engineering is rapidly evolving from traditional empirical experimentation toward data-driven intelligent bio-manufacturing. This transition has created an urgent need for engineers who are fluent in both biological sciences and artificial intelligence (AI), yet many undergraduate programs remain compartmentalized, leaving graduates without the computational literacy required for modern research and development. To address this skills gap, we developed a Tria
Bridging the digital divide in bio-manufacturing: construction and validation of an OBE-AI-BT integrated teaching framework using a modified Delphi method
Ju Guo
