Bigger Picture: AI-Driven Chemical Processes: From Human-in-the-Loop to Self-Optimising Labs

Speaker: Dr Antonio del Rio Chanona, Imperial College London - CEB alum

Abstract

Artificial intelligence offers a new path to chemical processes: enabling chemical systems that not only learn from data but also improve themselves over time.

In this talk, I will outline how AI can close critical gaps in process development and operation, paving the way towards autonomous, self-optimising laboratories and process plants. I will focus on three complementary algorithmic approaches. The first, Bayesian optimisation, provides a framework for experimental design and optimisation. I will particularly discuss how we can use multi-fidelity and human-in-the-loop strategies for a more informed process optimisation.

Second, I will discuss how large language models (LLMs) can and are being leveraged to capture human knowledge, interact with algorithms, and enable autonomous processes via symbolic reasoning and algorithmic search.

Finally, I will talk about how reinforcement learning, famous for making computers “learn” and beat the best humans in the world at various tasks, unlocks new opportunities for control and real-time optimisation of complex, dynamic processes, with particular promise in bioprocess applications. Together, these advances point to a unifying vision: AI-driven chemical processes that are faster to develop, safer to operate, and inherently more sustainable.

I will conclude by reflecting on the emerging paradigm of autonomous process innovation and the opportunities it creates for the chemical sciences and industry.

Part of the Bigger Picture Talk Series 

Speaker Bio:

Dr Antonio del Rio Chanona is an Associate Professor and head of the Optimisation and Machine Learning for Process Systems Engineering group at the Department of Chemical Engineering, Imperial College London.

His main research interests include Data-Driven Optimisation, Reinforcement Learning, Large Language Models and Hybrid Modelling applied to chemical systems. Antonio received his MEng from UNAM in Mexico and his PhD from the University of Cambridge, where he was awarded the Danckwerts-Pergamon Prize for the best doctoral thesis of his year.