About
I am currently a lecturer in Artificial Intelligence for particle accelerators at the University of Liverpool and a member of the Cockcroft Institute.
By training, I am an accelerator physicist, and I became fascinated by machine learning along the way. During my doctoral studies and fellowship, I worked with high-energy proton colliders at CERN, and later on with electron light sources. I was drawn to accelerator physics from an early stage due to its unique balance between theory and experiment—a balance I have experienced both through detailed simulation studies and by actively participating in beam operations during numerous "beam times" at various accelerators.
Machine learning introduces an exciting new dimension to the inherently multidisciplinary field of accelerator physics. My views on the role of machine learning in accelerator physics can be found here.
I am particularly interested in reinforcement learning, a unique paradigm inspired by fundamental principles of animal and human behaviour. This interest led me to co-found the Reinforcement Learning for Autonomous Accelerators (RL4AA) international collaboration, which organises targeted workshops featuring state-of-the-art tutorials each year.
I am also involved in Bayesian optimisation research. You can find the first review on Bayesian optimisation in particle accelerators here.
I value the power of collaboration and interdisciplinary research, and I actively seek partnerships with experts in reinforcement learning and generally control theory to enhance the scope and impact of my work. I welcome opportunities to collaborate with researchers, institutions, and industry partners.
I sporadically post on social media, you can find me on instagram.