Applications of Machine Learning to Process Chemistry

• Introduction to Foundational ML Concepts
• Computer Aided (Retro) Synthesis Prediction
• Bayesian Optimisation
• Reaction Selectivity Prediction
• Reaction Yield Prediction

The target audience is generalist chemists who want to learn more about this emerging field. No experience in coding, artificial intelligence or machine learning is assumed.

Attendees should note that topics such as Large Language Models, Computer Vision, and Intelligent Robotics are covered the “Applications of Artificial Intelligence to Process Chemistry” short course.

This course will provide attendees with an overview of how machine learning is being applied in process chemistry. A select set of case studies will be presented to illustrate state of the art applications. Strengths, weaknesses and gaps in the tools will be highlighted. Basic concepts of ML will be explained, and a curated list of references will provided for those who want to dig deeper into how the ML tools work. At the end of the course generalist chemists will be more able to read and comprehend the rapidly increasing body of literature being produced on ML applications to process chemistry, and hopefully they will be inspired to try some of the techniques themselves.