From Prediction to Profit: How Machine Learning and Optimization Create Advantage at Dow
The Texas A&M Energy Institute’s Distinguished Lecture Series in Energy will feature Dr. Birgit (Bea) Braun, an R&D/TS&D Fellow for Digital Innovation in the Packaging, Specialty Plastics & Hydrocarbons R&D organization at the Dow Chemical Company, on Wednesday, March 25, 2026, from 11:00 a.m. – 12:00 p.m. CDT (UTC -5:00) in the Frederick E. Giesecke Engineering Research Building (GERB) Third Floor Conference Room and through a Zoom Meeting. The topic will be “From Prediction to Profit: How Machine Learning and Optimization Create Advantage at Dow.”
Abstract
Machine learning has become a powerful tool for extracting insights from complex industrial data—but insight alone does not create value. In large‑scale chemical manufacturing and R&D environments, value is realized only when predictive models are embedded into constrained decision‑making processes that translate analytics into action.
This seminar explores how Dow combines machine learning, hybrid modeling, and mathematical optimization to move from prediction to profit across R&D, manufacturing, and asset management. Through real industrial case studies, the talk illustrates how inverse formulation design accelerates product development under regulatory and performance constraints; how hybrid physics‑informed models enable reliable prediction of hard‑to‑measure phenomena such as catalyst deactivation; and how large‑scale optimization supports high‑stakes decisions such as maintenance turnaround planning and capital allocation.
A central theme of the presentation is why “algorithms to money” is hard in practice. Safety‑critical systems, sparse and fragmented data, and highly constrained operating environments require more than accurate models—they require interpretable analytics, robust data foundations, and optimization frameworks that align with how engineers and operators make decisions. The talk concludes with lessons learned from deploying decision‑support tools at scale and a perspective on the organizational, data, and modeling capabilities needed to sustain value creation from advanced analytics in the process industries.
Biography
Birgit (Bea) Braun, Ph.D., is an R&D/TS&D Fellow for Digital Innovation in the Packaging, Specialty Plastics & Hydrocarbons R&D organization at Dow. Over nearly 15 years with the company, she has held diverse roles across R&D and M&E organizations, consistently driving innovation at the intersection of science and technology.
For more than a decade, Bea has focused on applying Artificial Intelligence (AI) and Machine Learning (ML) to chemical manufacturing and materials research. She has led the development and deployment of numerous data science solutions across Dow, and today her work centers on unlocking value through holistic digital transformation—while staying deeply connected to her passion for advancing AI/ML technologies impacting chemical processes and materials.
Bea earned a Dipl.-Ing. in Process Engineering with a specialization in Industrial Environmental Protection from Montanuniversität Leoben in Austria. She also holds an M.S. in Environmental Science & Engineering and a Ph.D. in Chemical Engineering from the Colorado School of Mines, where her research combined experimental and computational studies in polymer composites. Prior to joining Dow, Bea spent three years in a startup company focused on scaleup of biobased composites for packaging and specialty applications.
An active leader in the professional community, Bea serves as the Chair for the Industry 4.0 Topical at the AIChE Spring Meeting, overseeing more than 25 sessions. She has been involved with AIChE since 2017, previously serving as Sub-Topical Chair for Analytics & AI (2021–2023) and Co-Chair in 2023. Additionally, she contributed to the AIChE Southwest Process Technology Conference and is on the organizing committee for the 2026 Foundations of Process/Product Analytics and Machine Learning (FOPAM) conference.
Outside of work, Bea enjoys spending time with her husband and two children. An avid runner and outdoor enthusiast, she also loves bouldering, tennis, and other active pursuits.