Machine Learning in Chemical Science and Engineering

This course provides a theoretical and practical introduction to machine learning (ML) methods and their applications in chemistry, chemical engineering, and materials science. After a survey of ML algorithms, we will delve into specific applications (e.g., QSPR modeling, materials design, molecular simulation, process control, synthesis) to ascertain how ML methods, which are commonplace in Big Tech, are used in engineering. Students will explore state-of-the-art approaches through topical literature reviews and case studies and develop proficiency with algorithms (as deployed in an engineering context) via programming assignments.