Join the Process Development Division, September 5th at 03:00 PM EDT for our live webinar presentation, "Advances and Opportunities of AI and Machine Learning in Process and Product Design," hosted by Leo Chiang, Sr. R&D Digital Fellow at The Dow Chemical Company. Registration is open to all and can be accomplished here as well as via the button below.
Presentation Abstract:
To enhance safety, reliability, and productivity of industrial processes and to accelerate materials discovery, artificial intelligence (AI) and machine learning techniques have been widely used in process industries for many decades. In the current Industry 4.0 and digital era, AI propels advancement in a wide range of applications including image analytics, Natural language process (NLP), deep learning, reinforcement learning, hybrid modeling, and real-time analytics.
As more AI successes are demonstrated in process industries, there is a growing misconception that AI is to replace human decision. The talk will emphasize the need for of Responsible/Trustworthy AI and show industrial examples on how humans and AI must be working in the loop. One aspect is to understand how to incorporate AI methods to assist humans to accelerate discovery in research and to make well-informed decisions in manufacturing operations. The other aspect is to allow humans to incorporate engineering and science domain knowledge to make AI methods smarter. This talk aims to showcase success stories in process and product design, and it will offer insights into the future potential of generative AI and Large Language Models (LLMs). The discussion will extend to anticipated research paths, the necessity for workforce development, and the imperative collaboration between academia, technology providers, and the industry to further exploit AI's potential.
Speaker Bio:
Leo Chiang is a Senior R&D Digital Fellow at Dow Core R&D. He has a broad research interest in emerging AI and Data Science approaches and his ambition is to guide the industry to achieve AI at scale. Leo is on a mission to improve data acumen for workforce at all levels at Dow; he co-developed data science training program and championed many activities to foster cross functional collaboration. Leo is proactive in working with universities to support data science education in chemical engineering and the broader STEM community.
Leo has a B.S. degree from University of Wisconsin at Madison and M.S. and Ph.D. degrees from the University of Illinois at Urbana-Champaign, all in Chemical Engineering. Leo has co-authored 2 books, over 60 externally refereed journal/proceedings papers and has given over 150 conference presentations and university lectures.
Leo is a Fellow of American Institute of Chemical Engineers (AIChE) and has served as 2014-2016 Computing and Systems Technology (CAST) director, 2016 CAST 10E programming chair, 2017-2018 spring meeting program chair (MPC), and 2019-2022 Executive Board of the Program Committee (EBPC). Leo was instrumental in setting up the Big Data Analytics Topical Conference (2015 to 2017) and Industry 4.0 Topical Conference (2018-2020) at the spring meeting. He was recognized by the AIChE with the 2016 Herbert Epstein Award for his programming leadership and 2016 Computing Practice Award for his world-class leadership in the development and application of methodologies in analytics for batch and continuous processes known as Big Data.
Leo is also active in the broader engineering and control community, he was elected to the National Academy of Engineering (NAE) in 2023 and recognized by American Automatic Control Council with the 2020 Control Engineering Practice Award. He currently holds positions as a trustee of Computer Aids for Chemical Engineering (CACHE), a board member of the National Academies' Board on Chemical Sciences and Technology (BCST), the industry co-chair for the 2025 Dynamics and Control of Process Systems (DYCOPS) conference, and as the program chair for the 2026 Foundations of Process/Product Analytics and Machine learning (FOPAM) meeting.
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