Application of Generative AI in Bioprocess Engineering

3 units

This course will cover following topics on large language models (LLMs) and their application for bioprocess engineering and synthetic biology: 1) LLMs (online or local) introductions and comparison (GPT4o and Qwen); 2) Data security and API for safe LLM applications; 3) Trustworthy information collection, prompt engineering for information retrieval from synthetic biology literature; 4) Knowledge graph and RAG; 5) Feature engineering and data organization for text analysis of synthetic biology paper; 6) LLMs-driven machine learning of omics data; 7) Integrative LLMs with metabolic modeling. This class will also include research projects on the use of generative AI to assist metabolic engineering. Students will obtain essential skills to properly use LLMs (such as GPT4o) for advanced metabolic modeling, optimal experimental design, and knowledge synthesis.