ChE 2026 Spring Seminar Series – Faruque Hasan, PhD

Details

Speaker: Faruque Hasan, PhD

Title: Bridging Scales with Physics-Constrained Machine Learning

Abstract:
Mathematical modeling is a cornerstone of chemical engineering with applications ranging from molecular property prediction to process simulation and control to supply chain optimization. First-principles based models can be accurate but they are often computationally demanding to solve. On the other hand, data-driven surrogate models are computationally fast, but may not have the desired accuracy. In multiscale problems, we have the additional challenge of combining multiple models. This poses a central question: What is the best modeling paradigm for multiscale optimization? To that end, physics-constrained scientific machine learning has recently emerged as a powerful hybrid modeling technique to embed first principles-based domain knowledge directly into data-driven learning processes. In this talk, I will describe our recent works on physics-constrained neural networks and highlight how they can be applied to integrate different length and time scales for multiscale optimization towards uncovering new molecules, materials and processing pathways for the chemical industry. I will draw examples from a range of multiscale applications.

Bio:
Dr. Faruque Hasan is the Margaret ’85 and Graham Bacon ’85 Engineering Excellence Professor in Chemical Engineering at Texas A&M University, and Associate Director of the Texas A&M Energy Institute. He received his B.Sc. in Chemical Engineering from Bangladesh University of Engineering & Technology in 2005 and a Ph.D. from National University of Singapore in 2010. After a postdoctoral fellowship at Princeton University, he joined Texas A&M University in 2014. His research interests include scientific machine learning and nonlinear optimization with applications to hybrid modeling, integrated molecular and process design, computer-aided process intensification, and multiscale energy systems engineering. Professor Hasan is the recipient of an NSF CAREER award, Outstanding Young Researcher Award from the AIChE Computing and Systems Technology (CAST) Division, I&ECR Class of Influential Researchers, both Doctoral New Investigator Award and New Directions Award from ACS Petroleum Research Fund, and Best Paper Awards from Computers & Chemical Engineering and Journal of Global Optimization. He currently serves as the Second Vice Chair of the AIChE CAST Division and will assume the role of Division Chair in 2028.