Particle accelerators are one of the most complex machines in the world and the challenging research programmes of the next decades can only be met with technological innovation. Machine learning methods are a promising technology to not only assist accelerators but to fundamentally change the way they are designed and operated, entering a new era of autonomous and user-driven facilities. I currently work on researching and testing machine learning methods to solve relevant problems in particle accelerators. If you want to read more about this topic you can check this.
PhD in Accelerator Physics, 2018
École Polytechnique Fédérale de Lausanne
Licenciatura en Física, 2014
Universidad Autónoma de Madrid