Unlike traditional pharmaceuticals, biopharmaceuticals use living organisms, e.g., cells, as factories to provide essential life-saving treatments for severe and chronic diseases (including cancers, metabolic diseases, and infectious diseases such as COVID-19) often with advantages such as increased efficacy and reduced side effects. However, current manufacturing systems lack the flexibility to produce existing and new biopharmaceuticals on demand. This is mainly because biomanufacturing processes are highly complex and variable, with hundreds of biological, physical, and chemical factors dynamically interacting at molecular, cellular, and macroscopic scales. Further, bioprocessing mechanisms are not systematically understood, and data are often very limited, sparse, and heterogeneous. To address these challenges, this Faculty Early Career Development (CAREER) project aims to optimize biomanufacturing processes via a bioprocess-specific AI that integrates uncertainty, intelligence, and science (i.e., systems and synthetic biology). Leveraging emerging sensing technologies that can monitor bioprocesses at molecular and cellular scales, this AI can also efficiently decode fundamental mechanisms. Moreover, by transferring this AI to industry practice, it is hoped this research will help make life-saving biopharmaceuticals rapidly available by accelerating biomanufacturing systems integration and automation with dramatically improved capabilities. The project will in parallel c