Artificial Intelligence in Chemical Engineering: Past, Present, and Future
The next presentation in the Texas A&M Energy Institute Lecture Series, featuring Dr. Venkat Venkatasubramanian, the Samuel Ruben-Peter G. Viele Professor of Engineering in the Department of Chemical Engineering, Professor of Computer Science (Affiliate), and Professor of Industrial Engineering and Operations Research (Affiliate) at Columbia University, will be held on Wednesday, April 6, 2022, from 11:00 a.m. – 12:00 p.m. CDT (GMT -5:00) in the Frederick E. Giesecke Engineering Research Building (GERB) Third Floor Conference Room and through a Zoom Meeting. The topic will be “Artificial Intelligence in Chemical Engineering: Past, Present, and Future.”
Artificial intelligence (AI) started off with great promise in the early 1980s, spurred by the success of the expert system paradigm in certain applications. This prompted a flurry of research activities in chemical engineering in the mid-1980s. However, as the ensuing three decades showed, AI didn’t quite live up to its promise in chemical engineering.
So, what went wrong with AI?
In this talk, I will review the different phases of AI in chemical engineering over the last 35 years, providing some background and explanation to this question. I will also argue that this time it is different – I believe the time for AI in chemical engineering, and in other domains, has arrived, finally. There are many applications that are ready to yield quick successes in this new data science phase of AI. I will highlight recent work in materials design and in process operations as examples of exciting progress. However, the really interesting and intellectually challenging problems lie in developing such conceptual frameworks as hybrid models, mechanism-based causal explanations, domain-specific knowledge discovery engines, and analytical theories of emergence. These breakthroughs would require going beyond purely data-centric machine learning, despite all the current excitement, and leveraging other knowledge representation and reasoning methods from the earlier phases of AI. They would require a proper integration of symbolic reasoning with data-driven processing. I will discuss these challenges and opportunities going forward.
Professor Venkat Venkatasubramanian is Samuel Ruben-Peter G. Viele Professor of Engineering in the Department of Chemical Engineering, Professor of Computer Science (Affiliate), and Professor of Industrial Engineering and Operations Research (Affiliate) at Columbia University. He earned his Ph. D. in Chemical Engineering at Cornell, M.S. in Physics at Vanderbilt, and B. Tech. in Chemical Engineering at the University of Madras, India. He taught at Purdue University for 23 years, before returning to Columbia in 2011.
Venkat is a complex-dynamical-systems theorist interested in developing mathematical models of their structure, function, and behavior from fundamental conceptual principles. His natural tendency is to conduct curiosity-driven research in a style that might be considered impressionistic, emphasizing conceptual issues over mere techniques. He strives to create a simplified but essentially correct model of the reality that he studies. Venkat’s research interests are diverse, ranging from AI to systems engineering to theoretical physics to economics, but they are generally focused on the theme of understanding complexity and emergent behavior in different domains.
Venkat received the Norris Shreve Award for Outstanding Teaching in Chemical Engineering three times at Purdue University. He won the Computing in Chemical Engineering Award from AIChE and is a Fellow of AIChE. In 2011, the College of Engineering at Purdue University recognized his contributions with the Research Excellence Award. He is a past-President of the CACHE Corporation. He currently serves as an Editor for Computers and Chemical Engineering. His new book, How Much Inequality is Fair? Mathematical Principles of a Moral, Optimal, and Stable Capitalist Society, was published in 2017. Venkat’s other interests include comparative theology, classical music, and cricket.