Prodromos Daoutidis Delivers the 32nd Roger Sargent Lecture at Imperial College London
On December 4th, 2025, CEMS Professor Prodromos Daoutidis delivered the 32nd annual Roger Sargent Lecture at The Sargent Centre for Process Systems Engineering at Imperial College London. This lecture series, established in 1994, celebrates Professor Roger W. H. Sargent’s legacy, who—alongside the University of Minnesota’s Rutherford Aris and Neal Amundson—was a foundational figure in Process Systems Engineering. Professor Daoutidis now joins a distinguished lineage of influential scholars who were recognized with this lectureship, including Rutherford Aris himself, who delivered the very first Sargent Lecture.
Lecture Title: New Paradigms for the Automated Solution of Complex Control and Optimization Problems
Abstract
This talk will focus on the classic open challenge of solving complex, large-scale control and optimization problems efficiently and in an automated fashion. Such problems arise in process design and control due to process or plant integration and in the context of enterprise-wide optimization. Despite their complexity, they typically have structure and sparsity, which lends itself naturally to decomposition-based solution approaches. Yet finding proper decompositions has been addressed largely based on intuition.
We have developed methods based on modern network science that generate automatically high-quality decompositions that can be integrated directly in structured solution approaches. These methods rely on detecting latent block structures (communities and hierarchies) in suitable graph representations of control and optimization problems. I will describe the theoretical and algorithmic advances, and applications to plantwide control and integration of scheduling and dynamic optimization problems, along with an industrial implementation.
I will also discuss newly developed methods, based on machine learning, for aiding the selection and implementation of solution algorithms and accelerating process control and optimization. Collectively, these results highlight how advances in data and computer science can enable novel methods to address complex process systems engineering problems, very much in the spirit of Professor Sargent’s overarching research philosophy and legacy.
To learn more about Professor Daoutidis’s work, visit his research group’s website.