FOPAM 2026: Advancing Process and Product Analytics, Machine Learning, and AI in Chemical Engineering

The third Foundations of Process/Product Analytics and Machine Learning (FOPAM 2026) conference was held July 26–30, 2026, in Decatur, Georgia. Organized by CACHE in collaboration with AIChE, the meeting attracted 81 participants from academia, industry, and government laboratories, including 24 graduate students, 3 postdoctoral researchers, 19 faculty members, and approximately 35 industrial participants. The conference featured a pre-conference workshop, six technical sessions, invited presentations, panel discussions, and 33 poster presentations. The technical program covered a broad range of topics, including process monitoring and control, process optimization, molecular and materials discovery, product design, industrial applications of data analytics and machine learning, and engineering education and workforce development. Industrial presentations highlighted applications in chemical and pharmaceutical manufacturing, illustrating how advances in analytics, machine learning, and artificial intelligence (AI) are being translated into practical engineering solutions.

A central theme throughout the meeting was the importance of integrating data-driven methods and emerging AI capabilities with fundamental chemical engineering principles to develop reliable, interpretable, and effective approaches to process and product development. Discussions explored advances in hybrid modeling, digital twins, adaptive experimentation, optimization, generative AI, and AI-enabled decision support, while emphasizing the continued importance of engineering judgment and physical understanding. The conference provided opportunities for interaction and collaboration among industrial practitioners, academic researchers, and students, supported by the National Science Foundation and sponsors from industry and academia Sponsors from industry and academia included Lubrizol, Shell, Johnson & Johnson, Merck, Georgia Tech, Auburn University, and Princeton University.

Conference abstracts and presentations are available through the open-access: FOPAM 2026 proceedings published by PSE Press. Planning is underway for FOPAM 2028, tentatively scheduled for July 24–28, 2028, in Philadelphia, Pennsylvania, continuing the conference's tradition of bringing together academia and industry to advance process and product analytics, machine learning, and AI applications across the chemical engineering enterprise.