Teaching Artificial Intelligence to Chemical Engineers

Experience from a 35-year-old Course

Authors

  • Venkat Venkatasubramanian Columbia University

DOI:

https://doi.org/10.18260/2-1-370.660-130423

Abstract

The motivation, philosophy, and organization of a course on artificial intelligence in chemical engineering is presented. The purpose is to teach undergraduate and graduate students how to build AI-based models that incorporate a first principles-based understanding of our products, processes, and systems. This is achieved by combining symbolic AI with data-driven numeric AI. In this respect, this course is different from the standard machine learning course, which typically does not address the symbolic AI component.

Author Biography

Venkat Venkatasubramanian, Columbia University

Venkat Venkatasubramanian is the Samuel Ruben-Peter G. Viele Professor of Engineering in the Department of Chemical Engineering at Columbia University. He considers himself an artist in science, whose natural tendency is to conduct curiosity-driven research in a style that might be considered impressionistic, emphasizing conceptual issues over mere techniques. Venkat’s research interests are diverse, ranging from AI to systems engineering to theoretical physics to economics, but with a focus on understanding complexity and emergent behavior in different domains. 

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Published

2022-10-25

Issue

Vol. 56 No. 4 (2022): Fall 2022

Section

Manuscripts