Machine learning, artificial intelligence, and other forms of computer assistance have the potential to augment human intuition about chemical reactivity to accelerate scientific discovery. There are many applications of computer-aided chemistry relevant to catalysis and reaction engineering, from developing quantitative structure-activity/property relationships for model-guided optimization to building statistical models able to describe chemical reactions at the molecular or atomistic level. In this talk, I will highlight recent work applying AI/ML to reaction engineering and share some thoughts on future directions for the field.
