AI-Driven Chemical Processes: From Human-in-the-Loop to Self-Optimising Labs
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AI-Driven Chemical Processes: From Human-in-the-Loop to Self-Optimising Labs
Wed, 08/10/2025 - 14:00 to 15:30
Location:
Speaker:
Dr Antonio Del Rio Chanona
Affiliation:
Imperial College London
Synopsis:
IMPEE is delighted to host the IChemE Medal Winner’s Lecture in collaboration with ICS. Dr. Antonio Del Rio Chanona, recipient of the 2025 IChemE Junior Sargent Medal, is an Associate Professor at Imperial College London and Director of the Optimisation and Machine Learning for Process Systems Engineering Group (OptiML PSE).
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. Thie 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.
Biography:
Antonio del Rio Chanona is 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. He received the EPSRC fellowship to adopt automation and intelligent technologies into bioprocess scale-up and industrialization and has received awards from the International Federation of Automatic Control (IFAC), the Institution of Chemical Engineers (IChemE) and the the Association of European Operational Research Societies (EURO) in recognition for research in areas of process systems engineering, industrialisation of bioprocesses, and adoption of intelligent and autonomous learning algorithms to chemical engineering.
Antonio is very enthusiastic about teaching and mentoring. He is the Director of Education for the Sargent Centre, has organized several summer schools, included The Data Driven Optimization Summer School (2022), Machine Learning for Chemical Engineering Summer School (2023), Bayesian Optimisation Summer School (2024), amongst others.