Latest Events

Speaker: Joe Saffer, Senior Product Analyst, Aurora Energy 

Speaker: Tony Roulstone, University of Cambridge Lecturer Nuclear Engineering

In this talk, we identify the barriers to nuclear competitiveness, before examining the ways of making existing designs, the more recent SMRs and advanced technologies succeed. In each case, we look at the facts, the opportunities and the prospects for delivering the nuclear promise inherent in the resurgence of interest in nuclear energy.

Tony Roulstone has broad experience of Aerospace, Power, Defence and Systems sectors in a diverse environment. He lectures in Nuclear Energy at University of Cambridge and is a founder of the Department of Engineering’s Nuclear Energy MPhil programme.

He’s led successful business transformation across whole of a major multinational company delivering major cost reduction & cash savings and developed diverse group of high technology businesses strategically repositioning businesses & growing both the group’s market share & its profit.

This talk is in-person and not delivered remotely.

This talk is part of the Engineering Department Nuclear Energy Seminars series.

If you have a question about this talk, please contact Helene Jones.

Speaker: Professor Clare Grey, Department of Chemistry, University of Cambridge

AMET Seminars on the Energy Transition

Speaker: Simon Taylor (University of Cambridge & EPRG)

EPRG Energy & Environment Seminars Michaelmas Term 2025 Tuesdays fortnightly at 12.30-1.30pm (in-person) Please contact EPRG Administrator (eprgadm@jbs.cam.ac.uk) for further details

Seminar organizer: Zeynep Clulow(z.clulow@jbs.cam.ac.uk)

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.