CHE 626 - Applications of Machine Learning

This course provides an overview of the core theory and implementation of cutting-edge applications of machine learning in chemical engineering including methods in deep learning (e.g., convolutional neural networks), Bayesian optimization, and reinforcement learning. Application areas are based on traditional and emerging industrial practice which include (but are not limited to) process control, process design, process scheduling, material discovery, process monitoring, and fault detection.